Mon, May 18 Link
8:30 AM - 9:20 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Julianne Chung | A new age of iterative Krylov methods for inverse problems: What to do with expensive inner-product computations? | McBryde Hall 100 | Krylov methods; Golub-Kahan; randomized algorithms |
9:25 AM - 10:15 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Hugo Woerdeman | Optimal interpolation in Hardy, Bergman and $\ell^p_A $ spaces: a reproducing kernel Banach space approach | McBryde Hall 100 | interpolation; optimization; polynomials |
11:00 AM - 11:25 AM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Delio Jaramillo Velez | Connected domination and the v-number of binomial edge ideals | Goodwin Hall 135 | graph theory; graph invariants; connected | |
| Igor Simunec | Restoring similarity in randomized Krylov methods with applications to eigenvalue problems and matrix functions | Torgersen Hall 3100 | Krylov methods; Arnoldi; eigensolvers | Very Likely |
| Dona Ishara Saparamadu | Krylov Methods for Rank-one Updates of Eigenvalue Problems and Linear Equations | McBryde Hall 129 | Krylov methods; Arnoldi; eigensolvers | |
| Maria Isabel Bueno Cachadina | Redesigning Assessment in Applied Linear Algebra in the Age of Generative AI | Torgersen Hall 2150 | education; generative AI; SVD | Possible |
| Daniel Szyld | Convergence of Randomized and Greedy Block Gauss-Seidel methods, as well as Asynchronous Iterations | Torgersen Hall 1040 | randomized algorithms; parallel computing; convergence | |
| Vanni Noferini | Nearest matrix with multiple eigenvalues by Riemannian optimization | Torgersen Hall 1030 | optimization; matrix nearness; manifolds | |
| Andreas Tataris | Reduced order models for inverse scattering | Goodwin Hall 145 | inverse problems; model reduction; optimization | |
| Adela DePavia | Understanding and Leveraging Adaptive Algorithms’ Sensitivity to Change-of-Basis | McBryde Hall 113 | randomized algorithms; machine learning; optimization | |
| Linda Patton | Matrix numerical ranges of Toeplitz operators with polynomial symbols | Goodwin Hall 155 | model reduction; numerical range; polynomials | |
| Ethan Epperly | Computational linear algebra from time evolution and noisy inner products | Goodwin Hall 115 | eigensolvers; model reduction; quantum linear algebra | |
| Alex Gorodetsky | Optimal tensor network structure search | Torgersen Hall 1060 | education; tensor methods; model reduction | |
| Nathan Lindzey | An Eventown Result for Permutations | Goodwin Hall 125 | distance metrics; graph theory; coding theory |
11:25 AM - 11:50 AM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Juan Pablo Serrano Perez | The characterization of graphs with two trivial distance ideals | Goodwin Hall 135 | distance metrics; graph theory; graph invariants | |
| Emil Krieger | A general framework for Krylov ODE residuals with applications to randomized Krylov methods | Torgersen Hall 3100 | distance metrics; Krylov methods; Arnoldi | Very Likely |
| Jordan Jackson | Convergence Analysis for Infinite GMRES | McBryde Hall 129 | Krylov methods; GMRES; Arnoldi | Possible |
| Maria Trigueros | Blind Singal Separation as a model to introduce Linear Transformatios | Torgersen Hall 2150 | education; inverse problems; model reduction | |
| Mirjeta Pasha | Randomized Sketching for Tucker Tensors: From Compressed Summation to GMRES | Torgersen Hall 1040 | Krylov methods; GMRES; SVD | |
| Volker Mehrmann | Robustly asymptotically stable dissipative Hamiltonian descriptor systems | Torgersen Hall 1030 | distance metrics; matrix nearness; graph invariants | |
| Jörn Zimmerling | ROM-based Inverse Scattering for Monostatic Data | Goodwin Hall 145 | inverse problems; model reduction; optimization | |
| Kaustubh Roy | Fast and explainable clustering in the Manhattan and Tanimoto distance | McBryde Hall 113 | clustering; distance metrics; machine learning | |
| Nancy Menzelthe | Multiplicities and $k $-Numerical Range | Goodwin Hall 155 | numerical range; manifolds; multiplicity | |
| Zeguan Wu | Quantum Linear Algebra: from Optimization to Differential Equation | Goodwin Hall 115 | model reduction; optimization; PDEs | |
| Nico Vervliet | Decomposition of a tensor into multilinear rank-$(M_r,N_r,\cdot)$ terms | Torgersen Hall 1060 | tensor methods; model reduction; optimization | |
| Matteo Bertuzzo | A graph from the injection metric | Goodwin Hall 125 | distance metrics; model reduction; graph theory |
11:50 AM - 12:15 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Antwon Park | Smith Normal Forms of Graphical Hermite Simplices | Goodwin Hall 135 | graph theory; graph invariants; graphical | |
| Bowen Gao | A mixed precision algorithm for matrix root functions | Torgersen Hall 3100 | matrix functions; machine learning; mixed precision | Likely |
| Abigail Williams | Twin CG for Linear Equations with Multiple Right-hand Sides | McBryde Hall 129 | distance metrics; Krylov methods; Lanczos | |
| Megan Wawro | The Inquiry-Oriented Linear Algebra Project | Torgersen Hall 2150 | education; model reduction; iola | |
| Paul Cazeaux | Novel Randomized Tensor-Train Sketch and Applications | Torgersen Hall 1040 | Krylov methods; randomized algorithms; low-rank | |
| Simon Mataigne | Bounds on the geodesic distances on the Stiefel manifold for a family of Riemannian metrics | Torgersen Hall 1030 | distance metrics; model reduction; matrix nearness | |
| Yanfei Xiang | Numerical linear algebra with neural operator preconditioning for solving some parametric PDEs | McBryde Hall 113 | distance metrics; Krylov methods; GMRES | |
| Edward Poon | On the spatial numerical range | Goodwin Hall 155 | numerical range; range; spatial | |
| Mohammadhossein Mohammadisiahroudi | Quantum Linear Algebra for Optmization | Goodwin Hall 115 | model reduction; optimization; PDEs | |
| Eric Phipps | Synchronous and Asynchronous Parallelism Approaches for Generalized Canonical Polyadic Tensor Decomposition with GenTen | Torgersen Hall 1060 | tensor methods; optimization; stochastic matrices | |
| Michael Tait | Coding theory via graph theory | Goodwin Hall 125 | graph theory; coding theory; coding |
2:00 PM - 2:25 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Joel Louwsma | Generalized chip firing and critical groups of arithmetical structures on trees | Goodwin Hall 135 | graph theory; graph invariants; critical | |
| Ritesh Khan | Adaptive Mixed Precision Hierarchical Matrices | Torgersen Hall 3100 | low-rank; model reduction; mixed precision | |
| Wasin So | Graph Energy Change Under Edge Deletion | Goodwin Hall 155 | graph theory; graph; energy | |
| Victor Pan | Superfast 1-Norm Estimation | Torgersen 1020 | model reduction; superfast; norm | |
| Hayden Henson | Polynomial Preconditioning for Indefinite Matrices | McBryde Hall 129 | Krylov methods; GMRES; preconditioning | Possibly |
| Jessie Chen | Optimal Experimental Design for Gaussian Processes via Column Subset Selection | Torgersen Hall 1040 | randomized algorithms; model reduction; optimization | |
| Steven Miller | Random Matrix Ensembles with Split Limiting Behavior | Goodwin Hall 145 | distance metrics; model reduction; matrix equations | |
| Tim Mitchell | Reliably Computing the Worst-case H-infinity Norm of a Parametric System Using an Interpolation-based Algorithm. | Torgersen Hall 1030 | distance metrics; interpolation; optimization | |
| James Hazelden | Universal Kronecker Core Factorization of the NTK: Quantifying Implicit Bias of Gradient Descent | McBryde Hall 113 | randomized algorithms; low-rank; tensor methods | |
| Adam Byrne | Near-term quantum subspace diagonalization | Goodwin Hall 115 | Krylov methods; tensor methods; model reduction | |
| Julian Mangott | A Tree Tensor Network Integrator for the Chemical Master Equation | Torgersen Hall 1060 | low-rank; tensor methods; matrix functions | |
| Ken Duffy | Graph-based error correction code constructions made practical by modern decoder developments | Goodwin Hall 125 | graph theory; coding theory; code |
2:25 PM - 2:50 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Carlos Alfaro | The Smith normal form of distance matrices of high dimensional trees | Goodwin Hall 135 | distance metrics; graph theory; graph invariants | |
| Xinye Chen | Automated Precision Tuning for Numerical Algorithms | Torgersen Hall 3100 | optimization; precision; tuning | |
| Jitul Talukdar | On some Graphs determined by their Signless Laplacian spectrum | Goodwin Hall 155 | graph theory; signless; laplacian | |
| Victor Pan | Superfast Low Rank Approximation | Torgersen 1020 | low-rank; optimization; superfast | |
| Kingsley Michael | Polynomial Preconditioned Golub-Kahan for Finding Singular Values and Solving Least Squares | McBryde Hall 129 | Krylov methods; Golub-Kahan; SVD | Likely |
| Raf Vandebril | Accelerating Spectral Clustering of Time Series by approximating the Similarity Matrix using Randomly Pivoted Cholesky | Torgersen Hall 1040 | clustering; low-rank; time | |
| Motoyuki Nobori | On a characterization of the equality case in the generalized Böttcher-Wenzel inequality | Goodwin Hall 145 | quantum linear algebra; matrix equations; matrix inequalities | |
| Froilán M. Dopico | Distance to prescribed rank matrix polynomials via generic factorizations and alternating least squares | Torgersen Hall 1030 | distance metrics; matrix nearness; polynomials | |
| Haoran Ni | Principal Surjective Flows: Relaxing Bijection Assumption via the Smooth Co-Area Formula and Gram Determinants | McBryde Hall 113 | distance metrics; SVD; low-rank | |
| Ryan LaRose | Quantum Krylov methods with Hamiltonian powers | Goodwin Hall 115 | Krylov methods; randomized algorithms; quantum linear algebra | |
| Zhanrui Zhang | Low-Rank CP Tensor Compression and Its Application to High-Dimensional PDEs | Torgersen Hall 1060 | low-rank; tensor methods; optimization | |
| Shuxing Li | On the Hamming Weight Distribution of Cyclic Codes with Arbitrarily Many Nonzeroes | Goodwin Hall 125 | distance metrics; graph theory; coding theory |
2:50 PM - 3:15 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Ralihe Raul Villagran Olivas | From Chip Firing to Determinantal Ideals and Back | Goodwin Hall 135 | model reduction; graph theory; graph invariants | |
| Takeshi Terao | Iterative Refinement for a Subset of Eigenpairs of a Real Symmetric Matrix and Its Convergence Analysis | Torgersen Hall 3100 | distance metrics; eigensolvers; lambda | |
| Joonwon Seo | Row and Column Equivalence Transversality Properties: Extensions of the Rank-Preserving Transversality Property | Goodwin Hall 155 | manifolds; retp; cetp | |
| Achintya Sunil | Preconditioner Updating with Lasso-based Sparse Approximate Maps | McBryde Hall 129 | Krylov methods; preconditioning; inverse problems | Likely |
| Daniela Calvetti | Spotlight inversion by orthogonal projections | Torgersen Hall 1040 | inverse problems; model reduction; parameters | Likely |
| Fuzhen Zhang | Normal Matrices | Goodwin Hall 145 | matrix functions; matrix equations; polynomials | |
| Anshul Prajapati | Structured stability radii of dissipative Hamiltonian systems | Torgersen Hall 1030 | distance metrics; matrix nearness; graph invariants | |
| Eda Oktay | Reduced-and Mixed-Precision Algorithms for QR Decomposition | McBryde Hall 113 | QR; randomized algorithms; tensor methods | |
| Liron Mor Yosef | Quantum Matrix Encodings | Goodwin Hall 115 | matrix functions; model reduction; coding theory | |
| Polina Sachsenmaier | Iterative low-rank time integration of the time-dependent Schrödinger equation | Torgersen Hall 1060 | low-rank; tensor methods; matrix functions | |
| Kathryn Haymaker | Hierarchical quasi-cyclic codes from polynomial evaluation codes | Goodwin Hall 125 | distance metrics; low-rank; model reduction |
3:45 PM - 4:10 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Stephen Thomas | Constant Memory and Synchronization Costs for Nonsymmetric Krylov Methods | McBryde Hall 129 | distance metrics; Krylov methods; GMRES | |
| Thijs Steel | The accuracy of the QZ algorithm and some tricks to improve it | Torgersen Hall 1040 | eigensolvers; robustness; some | |
| Tahamina Akter | Scalable Approximate Selected Inversion via ILU and Spectral Corrections for Sparse Systems | Goodwin Hall 155 | distance metrics; low-rank; parallel computing | |
| Wei Gao | The sum of a topological index and its reciprocal index | Goodwin Hall 135 | distance metrics; graph theory; index | |
| Mykhailo Kuian | A Regularization Method for Compact Linear Operator Equations Based on the Arnoldi Process | Torgersen Hall 1030 | Krylov methods; Arnoldi; inverse problems | |
| Lauri Nyman | Convergence of flexible GMRES with and without randomized sketching | Goodwin Hall 115 | GMRES; randomized algorithms; convergence | Must |
| Conrad Plaut | Immersive Exercises for Linear Algebra | Torgersen Hall 2150 | education; generative AI; model reduction | |
| Subhayan Saha | Robustness of Minimum-Volume Nonnegative Matrix Factorization under an Expanded Sufficiently Scattered Condition | Torgersen Hall 1060 | low-rank; tensor methods; stochastic matrices | |
| John Peca-Medlin | Permutations induced by GEPP | Goodwin Hall 145 | distance metrics; model reduction; matrix equations | |
| Ilse Ipsen | Column subset selection: A new perspective | Torgersen Hall 3100 | QR; model reduction; polynomials | |
| Arjun Vijaywargiya | Inverse problems for history-enriched linear model reduction | Torgersen Hall 1020 | inverse problems; model reduction; graph invariants | |
| Kathryn Lund | The Fréchet derivative of the tensor t-function | McBryde Hall 113 | tensor methods; matrix functions; machine learning | |
| Leslie Hogben | The inverse symplectic eigenvalue problem of a graph | Goodwin Hall 125 | distance metrics; eigensolvers; graph theory |
4:10 PM - 4:35 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Yunhui He | A Generalized Alternating Anderson Acceleration Method | McBryde Hall 129 | machine learning; optimization; PDEs | |
| Vilhelm P. Lithell | From eigenvector nonlinearities to eigenvalue nonlinearities | Torgersen Hall 1040 | distance metrics; eigensolvers; model reduction | |
| Thomas Wick | Matrix-Free Geometric Multigrid Preconditioning Of Combined Newton-GMRES For Solving Phase-Field Fracture With Local Mesh Refinement | Goodwin Hall 155 | distance metrics; GMRES; preconditioning | |
| Nik Stopar | Combinatorial characterization of matrix algebras over finite fields | Goodwin Hall 135 | graph theory; combinatorial; compressed | |
| Toluwani Okunola | Recycling and Streaming for Large Scale Nonlinear Inverse Problems | Torgersen Hall 1030 | Krylov methods; inverse problems; model reduction | |
| Kyle Monette | New Insights into the Equivalence of Thick and Implicit Restarting Lanczos | Goodwin Hall 115 | distance metrics; Lanczos; Golub-Kahan | Must |
| Jeffrey Stuart | Finding the Right Basis (or Bases) | Torgersen Hall 2150 | education; SVD; QR | |
| Stefano Sicilia | Manifold-based Algorithms for the Hadamard Decomposition | Torgersen Hall 1060 | SVD; low-rank; tensor methods | |
| Mohsen Aliabadi | Stabilizer Fields and Dimension Growth in Product-Spans | Goodwin Hall 145 | matrix equations; stabilizer; theorem | |
| Cameron Musco | Structured Matrix Approximation via Matrix-Vector Products | Torgersen Hall 3100 | distance metrics; low-rank; model reduction | |
| Tomoki Koike | Efficient Streaming Operator Learning for Large-Scale Dynamical Systems | Torgersen Hall 1020 | SVD; model reduction; operator learning | |
| Mantas Mikaitis | Accurate Models of NVIDIA Tensor Cores | McBryde Hall 113 | tensor methods; machine learning; graph theory | |
| Brendan Rooney | Zero-Nonzero Patterns of Symmetric Orthogonal Matrices | Goodwin Hall 125 | distance metrics; graph theory; symmetric |
4:35 PM - 5:00 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Tom Werner | nlKrylov: A unified framework for nonlinear GCR-type Krylov subspace methods | McBryde Hall 129 | Krylov methods; GMRES; nonlinear | |
| Francoise Tisseur | Fast Algorithms for Optimal Damping in Mechanical Systems | Torgersen Hall 1040 | eigensolvers; tensor methods; optimization | |
| Ramakrishnan Kannan | Loracx: Low Rank Approximations with Constraints at Exascale | Goodwin Hall 155 | low-rank; stochastic matrices; parallel computing | |
| Chris Hart | The Rank-Preserving Transversality Property | Goodwin Hall 135 | distance metrics; graph theory; manifolds | |
| Riley Yizhou Chen | Latent Twin Operator | Torgersen Hall 1030 | inverse problems; model reduction; operator learning | |
| Antti Hannukainen | Domain decomposition method for eigenproblems | Goodwin Hall 115 | clustering; distance metrics; model reduction | Must |
| Martijn Boussé | Cards on the Table: Playing with Linear Algebra Concepts | Torgersen Hall 2150 | education; model reduction; game | |
| Damjana Kokol Bukovšek | Symmetric nonnegative trifactorization rank of matrices with a given pattern without a four cycle | Torgersen Hall 1060 | distance metrics; low-rank; tensor methods | |
| Marko Orel | From binary symmetric matrices to Coxeter-like graphs and self-dual codes | Goodwin Hall 145 | distance metrics; model reduction; graph theory | |
| John Urschel | How ill conditioned can sub-matrices of the Fourier matrix be? | Torgersen Hall 3100 | matrix functions; sub matrices; fourier | |
| Mattia Manucci | Solving Generalized Lyapunov Equations with guarantees: application to the Model Reduction of Switched Linear Systems | Torgersen Hall 1020 | model reduction; matrix equations; error | |
| Xiaobo Liu | Reduced Rank Extrapolation for Matrix Equations | McBryde Hall 113 | low-rank; model reduction; machine learning | |
| Luiz Emilio Allem | $q(G)$ for Threshold Graphs | Goodwin Hall 125 | graph theory; threshold; graphs |
5:00 PM - 5:25 PM
| Author | Title | Room | Keywords | Attend |
|---|---|---|---|---|
| Maria Vasilyeva | Accelerated local-global coupling for non-isothermal multiphase reactive flow in hydrate-bearing sediments | McBryde Hall 129 | flow; accelerated; local global | |
| Agnieszka Miedlar | From SCF to LOBPCG: Accelerated Solvers for Nonlinear Eigenvector Problems | Torgersen Hall 1040 | eigensolvers; model reduction; solvers | |
| Amit Upadhyay | Exploiting Kronecker Structure and Krylov Subspaces for Scalable Second-Order Optimization in Federated Physics-Informed Neural Networks | Goodwin Hall 155 | distance metrics; Krylov methods; model reduction | |
| Johnna Parenteau | On the Length of a Multiplicity List of a Graph | Goodwin Hall 135 | distance metrics; eigensolvers; model reduction | |
| Malena Sabate Landman | New flexible and inexact Krylov solvers for inverse problems | Torgersen Hall 1030 | Krylov methods; Golub-Kahan; preconditioning | |
| Paul Zachlin | Householder Sets and Relative Pseudospectra | Goodwin Hall 115 | pseudospectra; householder; sets | Must? |
| Gianfranco Verzella | Randomized algorithms for streaming low-rank approximation in tree tensor network format | Torgersen Hall 1060 | randomized algorithms; low-rank; tensor methods | |
| Tanvi Jain | Inequalities for different means of positive definite matrices | Goodwin Hall 145 | distance metrics; matrix equations; mean | |
| Stefan Güttel | Inner product-free approximation of matrix functions | Torgersen Hall 3100 | Krylov methods; GMRES; randomized algorithms | |
| Till Peters | $\mathcal{H}_2$ model order reduction for Bilinear Quadratic Output Systems | Torgersen Hall 1020 | interpolation; model reduction; optimization | |
| Stanislav Budzinskiy | Look-ahead mixed-precision inference of LLMs | McBryde Hall 113 | machine learning; inference; strategy | |
| Polona Oblak | How many eigenvalues of a tree can attain the maximum multiplicity? | Goodwin Hall 125 | distance metrics; graph theory; tree |
Tue, May 19 Link
8:30 AM - 9:20 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Arvind Krishna Saibaba | Stochastic trace estimation for parameter-dependent matrices | McBryde Hall 100 | distance metrics; inverse problems; model reduction |
9:25 AM - 10:15 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Jephian C.-H. Lin | Inverse problems on a graph: strong matrices and graph minors | McBryde Hall 100 | inverse problems; model reduction; graph theory |
11:00 AM - 11:25 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Chen Greif | A BFBt Preconditioner for Double Saddle-Point Systems | McBryde Hall 129 | distance metrics; preconditioning; schur |
| Kate Lorenzen | Spectrum of trees of diameter 4 for the distance Laplacian matrix | Goodwin Hall 135 | distance metrics; model reduction; graph theory |
| Yuxin Ma | Forward and backward error bounds for a mixed precision preconditioned conjugate gradient algorithm | Torgersen Hall 3100 | distance metrics; preconditioning; model reduction |
| Eugenio Turchet | Nearest correlation matrices with structure: a dynamical systems approach | McBryde Hall 113 | distance metrics; model reduction; optimization |
| Shweta Yadav | On the properties of solution sets of absolute value equations | Goodwin Hall 145 | stochastic matrices; properties; absolute |
| Fuzhen Zhang | A few issues in teaching linear algebra | Torgersen Hall 2150 | education; polynomials; issues |
| Xianqi Li | Conditional Denoising Diffusion Model-Based Robust MR Image Reconstruction from Highly Undersampled Data | Torgersen Hall 1040 | inverse problems; model reduction; diffusion |
| Punit Sharma | Constrained Rayleigh quotient optimization and its applications in polynomial eigenvalue problem | Torgersen Hall 1030 | distance metrics; eigensolvers; matrix functions |
| Petar Mlinarić | Least-squares Rational Approximation Using Riemannian Optimization | Torgersen Hall 1020 | Krylov methods; model reduction; optimization |
| Giacomo Antonioli | Efficient Encoding of Semiseparable Matrices in Quantum Circuits | Goodwin Hall 115 | QR; low-rank; tensor methods |
| Daniel Hayes | Efficient oversampled Tensor-Train approximations | Torgersen Hall 1060 | randomized algorithms; tensor methods; approximation |
| Aida Abiad | A unified framework for the Expander Mixing Lemma for graphs and its applications | Goodwin Hall 155 | eigensolvers; graph theory; stochastic matrices |
| Rafael D’Oliveira | Secure Distributed Matrix Multiplication | Goodwin Hall 125 | graph theory; coding theory; parallel computing |
11:25 AM - 11:50 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Xingjie Li | Robust Numerical Differentiation for Entropy-regularized Optimal Transport (EOT) with application to Shuffled Regression | McBryde Hall 129 | distance metrics; optimization; shuffled |
| Vilmar Trevisan | Advances on Brouwer’s Conjecture | Goodwin Hall 135 | graph theory; graph invariants; graph |
| Juan Zhang | Mixed Precision General Alternating-Direction Implicit Method for Solving Large Sparse Linear Systems | Torgersen Hall 3100 | model reduction; optimization; mixed precision |
| Dacian Bonta | Linear Geometry Insights in the Expectation Maximization Algorithm Convergence | McBryde Hall 113 | model reduction; graph theory; measurements |
| Lucas Siviero Sibemberg | A Classification of Seeds via the Minimum Number of Distinct Eigenvalues | Goodwin Hall 145 | distance metrics; model reduction; graph theory |
| Christine Andrews-Larson | Linear algebra applications in students’ post linear algebra course work | Torgersen Hall 2150 | education; model reduction; students |
| Oshani Jayawardane | A low-complexity locally recoverable matrix-influenced algorithm to globally recover codes | Torgersen Hall 1040 | distance metrics; model reduction; machine learning |
| Emre Mengi | Singular Value Characterizations for a Nearest Rectangular Polynomial Matrix with an Eigenvalue | Torgersen Hall 1030 | distance metrics; SVD; optimization |
| Reetish Padhi | Extensions of data-driven balancing to LQO and QB systems | Torgersen Hall 1020 | model reduction; balanced; truncation |
| Roel Van Beeumen | Efficient LCU block encodings through Dicke states preparation | Goodwin Hall 115 | SVD; coding theory; quantum linear algebra |
| Bhisham Dev Verma | Adaptive Randomized Tensor Train Rounding using Khatri-Rao Products | Torgersen Hall 1060 | GMRES; randomized algorithms; tensor methods |
| Shaun Fallat | Inverse Eigenvalue Problems for Graphs: The Weighted Laplacian Case | Goodwin Hall 155 | distance metrics; eigensolvers; graph theory |
| Kirsten Morris | Graph Properties of Codes from Dyadic and Quasi-Dyadic Matrices | Goodwin Hall 125 | model reduction; graph theory; coding theory |
11:50 AM - 12:15 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Andreas Mang | GA-NGMRES: An Alternating NGMRES Method for Accelerating First-Order Optimization | McBryde Hall 129 | Krylov methods; GMRES; preconditioning |
| Colby Sherwood | A representation theoretical approach to the p-rank of subset incidence matrices | Goodwin Hall 135 | distance metrics; graph theory; graph invariants |
| Mantas Mikaitis | Analysis of Floating-Point Matrix Multiplication Computed via Integer Arithmetic | Torgersen Hall 3100 | tensor methods; parallel computing; integer |
| Jonathan Tabares | Tensor Train-Compressed FDTD Solvers for Electromagnetic Simulations | McBryde Hall 113 | tensor methods; model reduction; PDEs |
| Guershon Harel | Promoting Linear Algebraic Reasoning Among Students: Affordances and Challenges | Torgersen Hall 2150 | education; model reduction; students |
| Vasilije Perovic | Computing Singular Values Above a Certain Threshold | Torgersen Hall 1040 | Lanczos; Golub-Kahan; SVD |
| Nicola Guglielmi | A Newton-bisection method with monotone convergence for matrix nearness problems. | Torgersen Hall 1030 | distance metrics; optimization; matrix nearness |
| Sam Bender | PIRKA: The Iterative Rational Krylov Algorithm for Linear Time-Periodic Systems | Torgersen Hall 1020 | Krylov methods; model reduction; optimization |
| Filippo Della Chiara | Practical block encodings of matrix polynomials that can also be trivially controlled | Goodwin Hall 115 | coding theory; quantum linear algebra; polynomials |
| Felice Manganiello | External codes for multiple unicast networks via interference alignment | Goodwin Hall 125 | graph theory; coding theory; field |
2:00 PM - 2:25 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Vladimir Druskin | Acceleration of Lanczos approximation for PDE discretizations in unbounded domains | Torgersen Hall 3100 | Krylov methods; Lanczos; randomized algorithms |
| Malena Espanol | Kronecker Rank Bounds for Operator Matrices | Torgersen Hall 1030 | inverse problems; PDEs; kronecker |
| Peter Semrl | Order automorphisms of effect algebras | Goodwin Hall 135 | order; automorphisms; effect |
| Martin Plávala | Today’s Experiments Suffice to Indirectly Verify the Quantum Essence of Gravity | Goodwin Hall 115 | model reduction; quantum linear algebra; entanglement |
| Zlatko Drmac | Numerical linear algebra for data driven nonlinear dynamics | Torgersen Hall 1020 | SVD; QR; model reduction |
| Charlotte Vermeylen | Reducing swamp behavior for canonical polyadic decomposition | Torgersen Hall 1060 | low-rank; tensor methods; model reduction |
| Xuzhou Zhan | On the stability criteria via finite Hankel matrices for regular matrix polynomials | Goodwin Hall 145 | matrix equations; stochastic matrices; polynomials |
| Ron Morgan | Polynomials, Twin BiCG and Approximating the Inverse | McBryde Hall 129 | distance metrics; Krylov methods; Lanczos |
| Shuai Shao | Concentrated real-pole uniform-in-time approximation of the matrix exponential | Torgersen Hall 1040 | interpolation; matrix functions; optimization |
| Kevin Vander Meulen | Sign patterns that require or allow the non-symmetric strong spectral property | Goodwin Hall 155 | distance metrics; eigensolvers; model reduction |
| Andrew Horning | Learning operators with continuous spectrum from data | McBryde Hall 113 | distance metrics; model reduction; operator learning |
| Valentino Smaldore | Spectral analysis of linear codes | Goodwin Hall 125 | distance metrics; graph theory; coding theory |
2:25 PM - 2:50 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Ibrohim Nosirov | Practical Spectral Density Estimation with Explicit Deflation | Torgersen Hall 3100 | distance metrics; Lanczos; eigensolvers |
| Nathaniel Pritchard | IterativeCUR: One Small Sketch for Big Matrix Approximations | Torgersen Hall 1030 | SVD; randomized algorithms; low-rank |
| Azam Mozaffarikhah | Polynomial Factorization via Matrix Representations | Goodwin Hall 135 | model reduction; polynomials; polynomial |
| Matthias Kleinmann | Time-evolution in generalized probabilistic theories | Goodwin Hall 115 | model reduction; quantum linear algebra; quantum |
| Cankat Tilki | Wavelet-Based Observables for Koopman Analysis: An Extended Dynamic Mode Decomposition Framework | Torgersen Hall 1020 | model reduction; graph invariants; koopman |
| David Thorsteinsson | Chiselling Algorithms for Algebraic Computation of Tensor Block Term Decompositions | Torgersen Hall 1060 | low-rank; tensor methods; model reduction |
| Dominique Guillot | Sharp lower bounds for generalized operator products | Goodwin Hall 145 | tensor methods; matrix equations; products |
| Daniele Toni | Preconditioned log-determinant approximation: one probe vector is almost always enough! | McBryde Hall 129 | distance metrics; Krylov methods; Lanczos |
| Linus Balicki | Multivariate Rational Approximation of Scattered Data Using the p-AAA Algorithm | Torgersen Hall 1040 | distance metrics; interpolation; polynomials |
| Jephian C.-H. Lin | Jacobian method and strong properties | Goodwin Hall 155 | distance metrics; eigensolvers; graph theory |
| Trevor Camper | Resolvent compactification methods for spectral approximation of Koopman operators | McBryde Hall 113 | eigensolvers; model reduction; operator learning |
| Pedro Paredes | Modern Expander-Based Error-Correcting Codes | Goodwin Hall 125 | graph theory; coding theory; quantum linear algebra |
2:50 PM - 3:15 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Rajarshi Bhattacharjee | Eigenvector Approximation via Random Sampling | Torgersen Hall 3100 | distance metrics; randomized algorithms; optimization |
| James Nagy | Regularized Krylov Subspace Methods in Low Precision | Torgersen Hall 1030 | Krylov methods; preconditioning; inverse problems |
| Koushik Bhakta | Pretty good state transfer in Grover walks on abelian Cayley graphs | Goodwin Hall 135 | graph theory; quantum linear algebra; polynomials |
| Hayato Arai | Quantum Simulation of Non-Positive-Operator-Valued Measurements in General Probabilistic Theories with Post-Selection and Prior Information. | Goodwin Hall 115 | model reduction; quantum linear algebra; stochastic matrices |
| Amy de Castro | Reduced order modeling and numerical linear algebra analogs | Torgersen Hall 1020 | distance metrics; interpolation; SVD |
| Alberto Bucci | Fast randomized compression of matrix-vector products in tensor-train format and applications to Krylov subspace methods | Torgersen Hall 1060 | Krylov methods; GMRES; randomized algorithms |
| Prateek Kumar Vishwakarma | Convolution of matrices: Cayley-Hamilton theory, matrix transforms, and positivity preservers, with connections to the Bruhat order | Goodwin Hall 145 | distance metrics; matrix functions; model reduction |
| Fabio Matti | Stochastic trace estimation for parameter-dependent matrices | McBryde Hall 129 | interpolation; Krylov methods; stochastic matrices |
| Karl Meerbergen | p-set valued AAA for parametric model order reduction. | Torgersen Hall 1040 | distance metrics; interpolation; model reduction |
| H Tracy Hall | A general strong property for IEP-G | Goodwin Hall 155 | distance metrics; eigensolvers; model reduction |
| Bohan Chen | Learning Enhanced Ensemble Filters: Continuum Limits of Attention on Measures | McBryde Hall 113 | distance metrics; operator learning; machine learning |
3:45 PM - 4:10 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Elle Buser | Natural Gradient Descent for Hyperparameter Estimation in Bayesian Inverse Problems | McBryde Hall 129 | distance metrics; inverse problems; machine learning |
| Michael Jones | The Restarted Block Two-Level Orthogonal Arnoldi Algorithm | Torgersen Hall 1040 | Krylov methods; Arnoldi; eigensolvers |
| Alexander Guterman | Frobenius theorem for Cullis determinant | Goodwin Hall 135 | model reduction; graph invariants; sigma |
| Etna Lindy | The Smith form of Sylvester and Bézout matrices for zero-dimensional ideals | Goodwin Hall 155 | matrix equations; polynomials; graph invariants |
| Ryo Takakura | Comparing measurement incompatibility via convex subsets of states | Goodwin Hall 115 | quantum linear algebra; incompatibility; measurement |
| Haibo Li | Scalable iterative data-adaptive RKHS regularization for linear inverse problems | Torgersen Hall 1030 | Krylov methods; Golub-Kahan; SVD |
| Asuman Oktaç | Linear Algebra Education from an APOS perspective | Torgersen Hall 2150 | education; model reduction; apos |
| Meiling Deng | T-Eigenvalues of Third-order Quaternion Tensors | Goodwin Hall 145 | eigensolvers; tensor methods; model reduction |
| Ioana Dumitriu | Divide-and-Conquer for Nonsymmetric Eigenvalue Problems Part I: Randomization | Torgersen Hall 3100 | distance metrics; eigensolvers; parallel computing |
| Cade Ballew | On linear matrix equations and the Akhiezer iteration | Torgersen Hall 1020 | Krylov methods; matrix functions; model reduction |
| Md Taufique Hussain | High-Performance Implementation of Star-M SVD for Big Data Compression | Torgersen Hall 1060 | SVD; tensor methods; optimization |
| John Byrne | Cycles in directed graphs | Goodwin Hall 125 | graph theory; digraph; cycles |
| George Stepaniants | Learning Material Constitutive Laws with Neural Operators | McBryde Hall 113 | operator learning; machine learning; PDEs |
4:10 PM - 4:35 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Zequn Zheng | Flattening and Middle Rank Tensor Approximation | McBryde Hall 129 | tensor methods; machine learning; optimization |
| Daniel Bielich | Integration of the GPLHR Method Within LS-DYNA | Torgersen Hall 1040 | eigensolvers; preconditioning; optimization |
| Elizabeth Dinkelman | Geometric and Combinatorial Properties of the ASM Polytope | Goodwin Hall 135 | distance metrics; graph theory; parallel computing |
| Steve Mackey | A Unified Framework for Linearizations of Matrix Polynomials in Classical Bases | Goodwin Hall 155 | polynomials; bases; linearizations |
| Jamie Sikora | Definitely Not That One: The Art of Antidistinguishing Quantum States | Goodwin Hall 115 | quantum linear algebra; quantum; states |
| Jonas Bresch | Stochastic zeroth-order calculation of operator quantities | Torgersen Hall 1030 | inverse problems; model reduction; stochastic matrices |
| Sima Ahsani | Engaging Undergraduates in Computational Linear Algebra Through Data-Driven Projects | Torgersen Hall 2150 | education; model reduction; machine learning |
| Jie Tian | Revisiting the Upper Bild Convexity of Quaternionic Numerical Range | Goodwin Hall 145 | distance metrics; numerical range; matrix equations |
| Ryan Schneider | Divide-and-Conquer for Nonsymmetric Eigenvalue Problems Part II: Implementation | Torgersen Hall 3100 | distance metrics; eigensolvers; randomized algorithms |
| Rudi Smith | A tangential low-rank ADI method for solving indefinite Lyapunov equations | Torgersen Hall 1020 | low-rank; model reduction; matrix equations |
| Fan Tian | Streaming Tensor BM-Decomposition | Torgersen Hall 1060 | tensor methods; tensor; streaming |
| Igor Balla | The factorization norm and an inverse theorem for MaxCut | Goodwin Hall 125 | QR; graph theory; norm |
| Esther Gallmeier | Data-efficient Adjoint-free Learning for Asymptotically Smooth Integral Operators | McBryde Hall 113 | low-rank; matrix functions; operator learning |
4:35 PM - 5:00 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Yunhui He | Accelerated Multigrid Cycles | McBryde Hall 129 | distance metrics; model reduction; PDEs |
| Alec Dektor | Inexact subspace projection methods for tensor eigenvalue problems | Torgersen Hall 1040 | Lanczos; eigensolvers; low-rank |
| Bryan Shader | Sparsity of a matrix and its inverse | Goodwin Hall 135 | distance metrics; model reduction; graph theory |
| Gustaf Lorentzon | The Polynomial Set Associated with a Fixed Number of Matrix-Matrix Multiplications | Goodwin Hall 155 | model reduction; polynomials; multiplications |
| Gereon Koßmann | Information-theoretic finite de Finetti theorems for quantum and beyond | Goodwin Hall 115 | distance metrics; tensor methods; quantum linear algebra |
| Amit Subrahmanya | Nonlinear OED with Column Subset Selection | Torgersen Hall 1030 | inverse problems; model reduction; optimization |
| Matthew Mauntel | You sunk my Battleship! Exploring Matrix Multiplication with a Linear Algebra Video Game | Torgersen Hall 2150 | education; distance metrics; model reduction |
| Fengjiao Liu | Riccati Differential Equations, State Transition Matrices, and State Covariance Matrices | Goodwin Hall 145 | distance metrics; model reduction; PDEs |
| Diana Halikias | Operator learning without the adjoint | Torgersen Hall 3100 | low-rank; model reduction; operator learning |
| Dan E. Folescu | Data-Driven Modal Truncation | Torgersen Hall 1020 | model reduction; system; modal |
| Vishwas Rao | POD-DEIM in the starM-product framework | Torgersen Hall 1060 | interpolation; tensor methods; model reduction |
| Emanuel Juliano | A graph energy conjecture through the lenses of semidefinite programming | Goodwin Hall 125 | graph theory; graph; energy |
| David Persson | Quasi-optimal hierarchically semi-separable matrix approximation | McBryde Hall 113 | randomized algorithms; low-rank; operator learning |
5:00 PM - 5:25 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Raymond Tuminaro | Algebraic Multigrid for H-Curl-Systems | McBryde Hall 129 | distance metrics; interpolation; PDEs |
| Luka Grubisic | Adaptive filtered subspace iteration for self adjoint eigenvalue problems on moving domains | Torgersen Hall 1040 | clustering; eigensolvers; subspace |
| Geir Dahl | A new combinatorial rank concept and its challenges | Goodwin Hall 135 | rank; concept; combinatorial |
| Julius Alexander Zeiss | Convergent Inner-outer Approximation Schemes From De Finetti Theorems For Games And Quantum Error Correction | Goodwin Hall 115 | distance metrics; QR; model reduction |
| Aryeh Keating | A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation | Torgersen Hall 1030 | inverse problems; model reduction; graph theory |
| Matthew Park | Symplectic Linear Algebra in Honors Linear Algebra -A Proposal | Torgersen Hall 2150 | education; randomized algorithms; symplectic |
| Joshua Cooper | Pressing sequences in nonbinary fields | Goodwin Hall 145 | distance metrics; graph theory; matrix equations |
| Heather Wilber | Spooky Scary Skeletons | Torgersen Hall 3100 | low-rank; model reduction; PDEs |
| Emmanuel Ameh | Model Reduction For Optimal Control By Balanced Truncation Of State and Gradient Covariance | Torgersen Hall 1020 | model reduction; optimization; control |
| Joe Kileel | Streaming data tensors efficiently and accurately | Torgersen Hall 1060 | low-rank; tensor methods; will |
| Henrique Soares Assumpção e Silva | Semidefinite programming bounds on fractional cut-cover and maximum 2-SAT for highly regular graphs | Goodwin Hall 125 | distance metrics; graph theory; matrix inequalities |
| Serkan Gugercin | L2-Optimal Reduced-Order Modeling Using Parameter-Separable Forms | McBryde Hall 113 | distance metrics; model reduction; operator learning |
Wed, May 20 Link
8:30 AM - 9:20 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Haim Avron | Quantum Numerical Linear Algebra Doesn’t Have to be Hard: A Matrix Algebra Oriented Approach | McBryde Hall 100 | matrix functions; model reduction; quantum linear algebra |
9:25 AM - 10:15 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Aida Abiad | The Eigenvalue Method in coding theory | McBryde Hall 100 | model reduction; graph theory; coding theory |
10:45 AM - 11:10 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Marc Aurèle Gilles | Low-Rank Approximation by Randomly Pivoted LU | Torgersen Hall 3100 | randomized algorithms; low-rank; approximation |
| Kévin Carrier | Decoding from the Other Side: Primal vs. Dual Attacks | Goodwin Hall 125 | distance metrics; model reduction; graph theory |
| Julio Moro | C-realizability in the Symmetric Nonnegative Inverse Eigenvalue Problem: a combinatorial characterization | Goodwin Hall 115 | distance metrics; eigensolvers; stochastic matrices |
| Yang Liu | Extension of hierarchical matrices to hierarchical tensors with butterfly compression | McBryde Hall 113 | low-rank; tensor methods; inverse problems |
| Ning Zheng | Randomized Generalized Error Minimizing Method for Linear Ill-Posed Problem | Torgersen Hall 1030 | Krylov methods; GMRES; Arnoldi |
| Günhan Caglayan | Visualizing the Spectral Theorem for Symmetric Matrices in a Dynamic Geometry Environment | Torgersen Hall 2150 | education; distance metrics; parallel computing |
| Geshuo Wang | Dynamical Tensor Train Approximation for Kinetic Equations | Torgersen Hall 1020 | low-rank; tensor methods; model reduction |
| Tianyun Tang | Stiefel Optimization is NP-hard | Goodwin Hall 135 | optimization; manifolds; stiefel |
| Shmuel Friedland | Norms on tensors in quantum information related to numerical radii | Goodwin Hall 145 | distance metrics; tensor methods; quantum linear algebra |
| Charbel Abi Younes | Spectral density estimation for random matrices | McBryde Hall 129 | Krylov methods; Lanczos; polynomials |
| Michael Ackermann | A refined nonlinear least-squares method for the rational approximation problem | Torgersen Hall 1040 | interpolation; model reduction; optimization |
| Rick Archibald | Streaming Compression of Scientific Data through Weak-SINDy and POD Integration | Torgersen Hall 1060 | tensor methods; matrix functions; model reduction |
| Carolyn Reinhart | Leaky Forcing of Unicyclic Graphs | Goodwin Hall 155 | eigensolvers; model reduction; graph theory |
11:10 AM - 11:35 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Mikhail Lepilov | Proxy Points and Rational Approximation Using Contour Integration | Torgersen Hall 3100 | randomized algorithms; low-rank; optimization |
| Veronika Kuchta | Post-Quantum Blind Signatures from Matrix Code Equivalence | Goodwin Hall 125 | distance metrics; model reduction; graph theory |
| Helena Šmigoc | Characteristic Polynomials of Nonnegative Hessenberg Matrices | Goodwin Hall 115 | distance metrics; eigensolvers; stochastic matrices |
| Robin Armstrong | Estimating High-Dimensional Covariance Matrices with Hierarchical Rank Structure | McBryde Hall 113 | low-rank; model reduction; covariance |
| Lucas Onisk | Mixed-to-Low Precision Iterative Methods for Linear Inverse Problems | Torgersen Hall 1030 | Krylov methods; inverse problems; mixed precision |
| Anna Davis, Paul Zachlin | A Free Online Linear Algebra Textbook with Explorations that may Help your Students | Torgersen Hall 2150 | education; model reduction; authors |
| Feliks Nueske | Tensor-based Dynamic Mode Decomposition for Complex Dynamics | Torgersen Hall 1020 | tensor methods; model reduction; tensor based |
| Tin-Yau Tam | Differential-Geometric View of the Schur–Horn Theorem and Related Convexity Phenomena | Goodwin Hall 135 | distance metrics; numerical range; schur horn |
| Tejbir Lohan | Linear maps preserving products of involutions | Goodwin Hall 145 | numerical range; graph invariants; involutions |
| Michele Rinelli | On block Krylov and matrix polynomials | McBryde Hall 129 | Krylov methods; Arnoldi; model reduction |
| Athanasios Antoulas | Descriptor realizations of multi-parameter systems and nonlinear eigenvalue problems | Torgersen Hall 1040 | interpolation; eigensolvers; polynomials |
| Leo Rebholz | Improving prediction for a low rank tensor ROM via continuous data assimilation | Torgersen Hall 1060 | tensor methods; model reduction; rank |
| Bonnie Jacob | Orientable forcing and relationships with linear algebra | Goodwin Hall 155 | eigensolvers; graph theory; graph invariants |
11:35 AM - 12:00 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Siting Liu | Kernel-Based Variational Formulations of Nonlocal Mean-Field Games | Torgersen Hall 3100 | randomized algorithms; inverse problems; model reduction |
| Rahmi El Mechri | Half is Enough: halving keys through optimal representation of self-orthogonal codes | Goodwin Hall 125 | matrix functions; model reduction; optimization |
| Miriam Pisonero | NIEP: positive and irreducible realizations | Goodwin Hall 115 | eigensolvers; graph theory; stochastic matrices |
| Abraham Khan | Parametric Hierarchical Matrix Approximations to Kernel Matrices | McBryde Hall 113 | distance metrics; low-rank; tensor methods |
| Malena Espanol | Separable Nonlinear Bayesian Inverse Problems | Torgersen Hall 1030 | inverse problems; uncertainty quantification; nonlinear |
| Sepideh Stewart | Balancing Theory and Application in Numerical Linear Algebra with Modern Computational Tools | Torgersen Hall 2150 | education; SVD; QR |
| David Bindel | Learning magnetic field structure from trajectories | Torgersen Hall 1020 | distance metrics; model reduction; field |
| Pálfia Miklós | Stochastic approximations with operator means | Goodwin Hall 135 | distance metrics; matrix functions; model reduction |
| Kennett Dela Rosa | On the $k $-numerical ranges of matrices | Goodwin Hall 145 | optimization; numerical range; range |
| Robbe Vermeiren | A Generalized Framework for Orthogonal Rational Functions applied to Rational Approximation | McBryde Hall 129 | clustering; Krylov methods; Arnoldi |
| Sean Reiter | The Loewner Framework Beyond Linear Outputs | Torgersen Hall 1040 | interpolation; model reduction; polynomials |
| Nick Alger | Derivative informed Tucker tensor train Taylor series surrogate models | Torgersen Hall 1060 | distance metrics; tensor methods; optimization |
| Mary Flagg | Parameters connected to the strong nullity interlacing property | Goodwin Hall 155 | distance metrics; eigensolvers; graph theory |
Thu, May 21 Link
8:30 AM - 9:20 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Sirani M. Perera | When Structured Matrices Pay Off: Linear Algebra at the Heart of Wireless Communication | McBryde Hall 100 | model reduction; machine learning; structured |
9:25 AM - 10:15 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Chi-Kwong Li | Numerical Ranges and Dilations: Theoretical Advances and Applied Perspectives | McBryde Hall 100 | quantum linear algebra; numerical range; break |
11:00 AM - 11:25 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Rodrigo San-José | Relative generalized Hamming weights and their applications in cryptography | Goodwin Hall 125 | distance metrics; graph theory; coding theory |
| Lorenzo Lazzarino | A-posteriori error estimates for randomized low-rank approximations | Torgersen Hall 3100 | randomized algorithms; low-rank; model reduction |
| Ludovick Bouthat | New Results on the Doubly Stochastic Inverse Eigenvalue Problem | Goodwin Hall 115 | distance metrics; eigensolvers; stochastic matrices |
| Chenyang Cao | Superfast and stable divide-and-conquer singular value decomposition for hierarchical rank-structured matrices | McBryde Hall 113 | distance metrics; SVD; low-rank |
| Chelsea Drum | Projected Regularization in Low Precision | Torgersen Hall 1030 | Golub-Kahan; inverse problems; mixed precision |
| Matthias Voigt | Adaptive kernel methods | Torgersen Hall 1020 | model reduction; kernel; dataset |
| Zhifeng Deng | Locally Diffeomorphic Logarithm of Special Orthogonal Matrices | Goodwin Hall 135 | distance metrics; matrix functions; inverse problems |
| Xiang Xiang Wang | Multiscale Grassmann Manifolds for Single-Cell Data Analysis | Torgersen Hall 1060 | distance metrics; tensor methods; manifolds |
| Rute Lemos | On the ellipticity of the higher rank numerical range | Goodwin Hall 145 | numerical range; higher; rank |
| Andrea Baleani | Computing Functions of Rank-structured or Telescopic Matrices. | McBryde Hall 129 | distance metrics; Krylov methods; SVD |
| Luka Marohnić | Rational quasi-Hermite approximation for computing acoustic quasiresonances in transmission problems | Torgersen Hall 1040 | interpolation; SVD; randomized algorithms |
| Caleb Cheung | Resolving Inverse Singular Value Problems with Spoiler Spaces | Goodwin Hall 155 | distance metrics; SVD; eigensolvers |
11:25 AM - 11:50 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Adam Downs | Code Rigidity in Characteristic 2 | Goodwin Hall 125 | model reduction; graph theory; coding theory |
| Hrvoje Olić | Randomized algorithms for operator trace estimation | Torgersen Hall 3100 | randomized algorithms; trace; varepsilon |
| Brando Vagenende | Eigenvalue regions and realising matrices for monotone stochastic matrices | Goodwin Hall 115 | model reduction; stochastic matrices; monotone |
| Christopher Wang | Unknown hierarchies, hyperbolic PDE, and randomized rank detection | McBryde Hall 113 | SVD; randomized algorithms; low-rank |
| Lassi Roininen | Bayesian inference for rough feature reconstructions | Torgersen Hall 1030 | inverse problems; uncertainty quantification; edges |
| Alejandro Diaz | Non-intrusive reduced-order models for parameterized partial differential equations using kernel methods | Torgersen Hall 1020 | distance metrics; interpolation; inverse problems |
| Xiang Lu | Special orthogonal, special unitary, and symplectic groups as products of Grassmannians | Goodwin Hall 135 | manifolds; grassmannians; special |
| Augustine (Runshi) Tang | Revisit CP Tensor Decomposition: Statistical Optimality and Fast Convergence | Torgersen Hall 1060 | tensor methods; model reduction; optimization |
| Brooke Randell | Numerical Range of Positive Hermitian Hankel Matrices | Goodwin Hall 145 | numerical range; hankel; range |
| Cooper Simpson | (Block) Lanczos Function Approximation for Quasi-Newton Optimization Algorithms | McBryde Hall 129 | Krylov methods; Lanczos; preconditioning |
| Leonie Van Pottelberghe | Tensor-based multivariate rational approximation | Torgersen Hall 1040 | interpolation; low-rank; tensor methods |
| Himanshu Gupta | The Inverse Symplectic Eigenvalue Problem and Coupled Zero Forcing for Graphs | Goodwin Hall 155 | eigensolvers; graph theory; graph invariants |
11:50 AM - 12:15 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Wendi Gao | Sample Complexity of the Matrix Code Equivalence Problem | Goodwin Hall 125 | model reduction; graph theory; coding theory |
| Brecht Verbeken | Spectrally Complete Subsets and Eigenvalue Regions of classes of Stochastic Matrices | Goodwin Hall 115 | eigensolvers; stochastic matrices; theta |
| Abraham Reyes Velazquez | Data-driven discovery of chemical reaction networks | Torgersen Hall 1030 | inverse problems; model reduction; PDEs |
| Peter Benner | Matrix Structures for Certified Stability of Nonlinear Reduced Models | Torgersen Hall 1020 | distance metrics; model reduction; machine learning |
| Nathan Henry | On the Identifiability of Transformer Self-Attention | Goodwin Hall 135 | generative AI; model reduction; machine learning |
| Andrew McCormack | The Nondecreasing Rank | Torgersen Hall 1060 | low-rank; tensor methods; stochastic matrices |
| Daisuke Hirota | The Cauchy Equation and Norm-Additive Mappings on Positive Cones of Commutative $C^{*}$-Algebras | Goodwin Hall 145 | distance metrics; model reduction; numerical range |
| Robert Webber | Everything is Vecchia: Unifying low-rank and sparse inverse approximations | McBryde Hall 129 | Krylov methods; low-rank; polynomials |
| Akil Narayan | Greedy rational approximation: Analysis and algorithms of sketched resolvents | Torgersen Hall 1040 | distance metrics; interpolation; SVD |
| Minerva Catral | An inverse eigenvalue problem for structured matrices determined by graph pairs | Goodwin Hall 155 | distance metrics; eigensolvers; graph theory |
2:00 PM - 2:25 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Sudipta Mallik | Spectral bounds for the clique number of a graph | Goodwin Hall 135 | graph theory; matrix inequalities; spectral |
| Michael Overton | On the Choice of Sign Defining Householder Transformations | McBryde Hall 129 | choice; sign; defining |
| DuBose Tuller | Newton’s Method for Computing the CP Decomposition | Goodwin Hall 115 | tensor methods; optimization; newton |
| Erkki Somersalo | Discretization-free Bayesian inverse problems | Torgersen Hall 1030 | inverse problems; uncertainty quantification; inverse |
| Jorge Reyes | Approximate Deconvolution and Spatial Filtering of Reduced Order Models for Fluid Flow | Torgersen Hall 1020 | model reduction; spatial; filtering |
| Alexander Mamonov | Multiparameter Waveform Inversion via Reduced Order Modeling | Goodwin Hall 145 | inverse problems; model reduction; optimization |
| Yidan Mei | Transform-Based Multilinear Algebra via Tensor Decompositions | Torgersen Hall 1060 | low-rank; tensor methods; tensor |
| Matt Burnham | Spectral theory of $K_t $-decomposable graphs | Goodwin Hall 125 | model reduction; graph theory; graphs |
| Heike Faßbender | Structure-preserving Krylov Subspace Approximations for the Matrix Exponential of Hamiltonian Matrices | Torgersen Hall 1040 | Krylov methods; matrix functions; hamiltonian |
| Hein Van der Holst | Multi-digraphs with maximum nullity at most one | Goodwin Hall 155 | eigensolvers; model reduction; graph theory |
| Aras Bacho | Operator Learning at Machine Precision | McBryde Hall 113 | inverse problems; model reduction; operator learning |
| Jocelyn Chi | Robust hybrid infinite and finite dimensional tensor factorizations | Torgersen Hall 3100 | randomized algorithms; tensor methods; tensor |
2:25 PM - 2:50 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Enide Andrade | Hermitian Spectra of Merged Subdivision Mixed Graphs | Goodwin Hall 135 | graph theory; graph invariants; mixed |
| David S Watkins | Fast computation of eigenvalues of periodic CMV matrices | McBryde Hall 129 | periodic; specified; time |
| Jingyu Liu | A Superfast Direct Solver of Type-III Inverse Nonuniform Discrete Fourier Transform Problem | Goodwin Hall 115 | preconditioning; nudft; direct |
| Lizuo Liu | Parametric Hyperbolic Conservation Laws: Learning Hyperbolic Conservation Laws from Data through Symmetrization. | Torgersen Hall 1030 | distance metrics; inverse problems; model reduction |
| Robin Herkert | Randomized Linear Algebra for Symplectic Model Order Reduction of Hamiltonian Systems | Torgersen Hall 1020 | SVD; randomized algorithms; model reduction |
| Fernando Guevara Vasquez | Characterization of the response of electric circuits with two kinds of passive elements | Goodwin Hall 145 | inverse problems; response; circuits |
| Anna Ma | Iterative methods for tensor systems under the t-product | Torgersen Hall 1060 | tensor methods; only; used |
| Isabel Byrne | Connectivity of distance-regular graphs | Goodwin Hall 125 | distance metrics; graph theory; brouwer |
| Ahmed Salam | On symplectic reduction of a matrix to upper $J $-Hessenberg form | Torgersen Hall 1040 | QR; reduction; such |
| Mark Hunnell | Tools for Determining the Minimum Rank of a Graph | Goodwin Hall 155 | distance metrics; eigensolvers; graph theory |
| Juan Felipe Osorio Ramirez | Operator Learning via Learned Differential Operators | McBryde Hall 113 | operator learning; PDEs; operator |
| Katherine Pearce | Randomized Numerical Linear Algebra for Tensor-Based Transformers | Torgersen Hall 3100 | randomized algorithms; tensor methods; attention |
2:50 PM - 3:15 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Aditya Khanna | How to Combinatorially Prove Matrices are Mutually Inverse | Goodwin Hall 135 | distance metrics; families; entries |
| Giacomo Antonioli | Quantum Spectral Methods for Poisson and Heat Equations | Goodwin Hall 115 | PDEs; coding theory; quantum linear algebra |
| Andrea Arnold | Interpolation-Based Estimation and Uncertainty Quantification of Periodic Time-Varying Parameters | Torgersen Hall 1030 | interpolation; inverse problems; model reduction |
| Sarswati Shah | Reduced Order Modeling of Conservation Laws via CDT | Torgersen Hall 1020 | distance metrics; model reduction; optimization |
| Mikhail Zaslavskiy | Adaptive data-driven reduced-order models of port-Hamiltonian dynamical systems for nonlinear inverse scattering applications | Goodwin Hall 145 | inverse problems; model reduction; optimization |
| Neriman Tokcan | Tensor Methods for Multi-omics Data | Torgersen Hall 1060 | low-rank; tensor methods; model reduction |
| Vishal Gupta | The non-existence of Moore polygons and spectral Moore bounds | Goodwin Hall 125 | QR; model reduction; graph theory |
| Nicole Joy Datu | The $\phi-$Reversibility Problem for the Real Symplectic Group | Torgersen Hall 1040 | model reduction; phi ; real |
| Mark Kempton | Graph Products to Achieve few Distinct Eigenvalues | Goodwin Hall 155 | eigensolvers; model reduction; graph theory |
| Gil Goldshlager | Towards High-Precision Optimizers for Scientific Machine Learning | McBryde Hall 113 | randomized algorithms; model reduction; operator learning |
| Karl Pierce | Blocked Leverage Score Sampling in the Randomized Alternating Least Squares CP Tensor Decomposition | Torgersen Hall 3100 | randomized algorithms; tensor methods; optimization |
3:15 PM - 3:40 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Eric de Sturler | Streaming Algorithms for Big Data Inverse Problems | Torgersen Hall 1030 | inverse problems; model reduction; parallel computing |
| Boris Kramer | Solution of generalized tensor Lyapunov equations arising in optimal control and model reduction | Torgersen Hall 1020 | tensor methods; model reduction; optimization |
| William Martin | Delsarte designs and Galois groups | Goodwin Hall 125 | graph theory; coding theory; scheme |
| Hemant Mishra | On generalization of Williamson’s theorem to real symmetric matrices | Torgersen Hall 1040 | distance metrics; symplectic; real |
| Dallin Seyfried | A Graphical Approach to Isospectral Unfoldings | Goodwin Hall 155 | eigensolvers; graph theory; quantum linear algebra |
| Christopher Beattie | Estimation for intrinsic Gaussian processes | McBryde Hall 113 | operator learning; parallel computing; intrinsic |
| Zichao Wendy DI | Accelerating Ptychographic Reconstruction via Stochastic Multilevel Optimization | Torgersen Hall 3100 | randomized algorithms; low-rank; inverse problems |
Fri, May 22 Link
8:45 AM - 9:10 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Freeman Slaughter | Code-Based Arithmetic Circuits | Goodwin Hall 125 | model reduction; graph theory; coding theory |
| Ela Đimoti | A More Robust Streaming Dynamic Mode Decomposition | Torgersen Hall 1040 | low-rank; tilde; decomposition |
| Chao Chen | An adaptive method for constructing hierarchical approximations and its application to inverse problems | McBryde Hall 113 | randomized algorithms; low-rank; inverse problems |
| Jonathan Lindbloom | Multigrid-Accelerated Sparsity-Promoting Projection Methods for Inverse Problems | Torgersen Hall 1030 | Krylov methods; preconditioning; inverse problems |
| Paul Van Dooren | Loewner linearizations of structured rational matrices | Torgersen Hall 1020 | distance metrics; interpolation; model reduction |
| Carmeliza Navasca | Tensor Data for Control Strategies in Systems | Torgersen Hall 1060 | tensor methods; model reduction; optimization |
| Chris Camaño | Tensor Network Krylov Methods: Algorithms, Theory Gaps, and Open Problems | McBryde Hall 129 | Krylov methods; GMRES; Lanczos |
| Bibhas Adhikari | Quantum-Classical Algorithms for Counting Triangles in a Signed Edge Stream | Goodwin Hall 115 | model reduction; graph theory; quantum linear algebra |
| Evan Coleman | Accelerating Asynchronous Iterative Methods with Residual-Biased Randomization | Torgersen Hall 3100 | randomized algorithms; model reduction; parallel computing |
9:10 AM - 9:35 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Hiram López | Code distances: a new family of invariants of linear codes | Goodwin Hall 125 | distance metrics; graph theory; coding theory |
| Aleksandr Malyshev | Fast and accurate solution of the periodic differential matrix Riccati equation | Torgersen Hall 1040 | distance metrics; eigensolvers; model reduction |
| Kate Wall | Circulant Preconditioning fractional PDEs on Adaptive Meshes | McBryde Hall 113 | clustering; preconditioning; low-rank |
| Diego Arenas Mata | Time-varying Bayesian Inverse Problems with Sparse Priors and Randomization | Torgersen Hall 1030 | randomized algorithms; preconditioning; inverse problems |
| Ion Victor Gosea | Tackling the curse of dimensionality through the parametric Loewner framework: recent advances and applications | Torgersen Hall 1020 | distance metrics; interpolation; tensor methods |
| Jeff Borggaard | Preconditioners for Kronecker Sum Systems with Applications to Polynomial Feedback Control | Torgersen Hall 1060 | preconditioning; tensor methods; model reduction |
| Alexander Hsu | Randomized Row Norm Estimation: Algorithms and Applications | McBryde Hall 129 | Krylov methods; randomized algorithms; matrix functions |
| Hanmeng Zhan | State transfer in discrete quantum walks: from coins to weighted graphs | Goodwin Hall 115 | model reduction; graph theory; quantum linear algebra |
| Mitchell Scott | Block Subset Selection based on Randomized QR with Column Pivoting | Torgersen Hall 3100 | QR; randomized algorithms; optimization |
9:35 AM - 10:00 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| William Mahaney | An Elementary Analysis of Multivariate Goppa Codes | Goodwin Hall 125 | distance metrics; model reduction; graph theory |
| Jiayu Bian | Spectral clustering and accelerated SSO for large and dense problem | Torgersen Hall 1040 | clustering; Arnoldi; SVD |
| Ichitaro Yamazaki | Adaptive coarse space for multi-level overlapping Schwarz preconditioners in FROSch | McBryde Hall 113 | eigensolvers; preconditioning; low-rank |
| Misha Kilmer | A Provably Convergent MM-GKS Variant for Large-Scale Image Reconstruction Problems | Torgersen Hall 1030 | Krylov methods; inverse problems; model reduction |
| Steffen W. R. Werner | From Structured Loewner Matrices to Balanced Mechanical Systems | Torgersen Hall 1020 | SVD; model reduction; PDEs |
| Anna Konstorum | A greedy approach for approximate tensor diagonalization | Torgersen Hall 1060 | distance metrics; tensor methods; tensor |
| Raphael Meyer | The Matrix-Vector Complexity of Ax=b | McBryde Hall 129 | Krylov methods; GMRES; randomized algorithms |
| Haixiao Wang | Singular values and vectors of sparse random rectangular matrices at criticality | Torgersen Hall 3100 | SVD; QR; randomized algorithms |
10:45 AM - 11:35 AM
| Author | Title | Room | Keywords |
|---|---|---|---|
| Sherry Li | Geometric and Algebraic Methods for Constructing Hierarchically Low-Rank Matrices | McBryde Hall 100 | distance metrics; low-rank; model reduction |
11:40 AM - 12:30 PM
| Author | Title | Room | Keywords |
|---|---|---|---|
| John Urschel | Nodal Statistics for Graphs and Matrices | McBryde Hall 100 | distance metrics; graph theory; parallel computing |