Soledad Villar

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 52

Top Topics

Linear Regression

Top Venues

IEEE Trans. Inf. Theory

Publications

Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
Towards fully covariant machine learning. Trans. Mach. Learn. Res. 2024 (2024)
Luana Ruiz, Ningyuan Teresa Huang, Soledad Villar
A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs. ICASSP (2024)
Ben Blum-Smith, Ningyuan Huang, Marco Cuturi, Soledad Villar
Learning functions on symmetric matrices and point clouds via lightweight invariant features. CoRR (2024)
Wilson Gregory, Josué Tonelli-Cueto, Nicholas F. Marshall, Andrew S. Lee, Soledad Villar
Learning equivariant tensor functions with applications to sparse vector recovery. CoRR (2024)
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning. ICLR (2024)
David W. Hogg, Soledad Villar
Is machine learning good or bad for the natural sciences? CoRR (2024)
Sharut Gupta, Joshua Robinson, Derek Lim, Soledad Villar, Stefanie Jegelka
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning. CoRR (2023)
Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
Fine-grained Expressivity of Graph Neural Networks. CoRR (2023)
Soledad Villar, David W. Hogg, Weichi Yao, George A. Kevrekidis, Bernhard Schölkopf
The passive symmetries of machine learning. CoRR (2023)
Soledad Villar, Benjamin Paul Chamberlain, Yuanqi Du, Hannes Stärk, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Yanqiao Zhu, Kexin Huang, Michelle M. Li, Sofia Bourhim, Ilia Igashov, Alexandre Duval, Mathieu Alain, Dominique Beaini, Xinyu Yuan
The Second Learning on Graphs Conference: Preface. LoG (2023)
Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris
Fine-grained Expressivity of Graph Neural Networks. NeurIPS (2023)
Wilson Gregory, David W. Hogg, Ben Blum-Smith, Maria Teresa Arias, Kaze W. K. Wong, Soledad Villar
GeometricImageNet: Extending convolutional neural networks to vector and tensor images. CoRR (2023)
Ningyuan Huang, Ron Levie, Soledad Villar
Approximately Equivariant Graph Networks. CoRR (2023)
Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu
Dimensionless machine learning: Imposing exact units equivariance. J. Mach. Learn. Res. 24 (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Ningyuan Huang, Ron Levie, Soledad Villar
Approximately Equivariant Graph Networks. NeurIPS (2023)
Luana Ruiz, Ningyuan Huang, Soledad Villar
Graph Neural Networks for Community Detection on Sparse Graphs. CoRR (2022)
Soledad Villar, Weichi Yao, David W. Hogg, Ben Blum-Smith, Bianca Dumitrascu
Dimensionless machine learning: Imposing exact units equivariance. CoRR (2022)
Nabeel Sarwar, Wilson Gregory, George A. Kevrekidis, Soledad Villar, Bianca Dumitrascu
MarkerMap: nonlinear marker selection for single-cell studies. CoRR (2022)
Carey E. Priebe, Ningyuan Huang, Soledad Villar, Cong Mu, Li Chen
Deep Learning is Provably Robust to Symmetric Label Noise. CoRR (2022)
Ningyuan Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman
From Local to Global: Spectral-Inspired Graph Neural Networks. CoRR (2022)
Ningyuan Huang, Soledad Villar
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants. CoRR (2022)
Charles Clum, Dustin G. Mixon, Soledad Villar, Kaiying Xie
Sketch-and-solve approaches to k-means clustering by semidefinite programming. CoRR (2022)
Ben Blum-Smith, Soledad Villar
Equivariant maps from invariant functions. CoRR (2022)
Efe Onaran, Soledad Villar
Shuffled linear regression through graduated convex relaxation. CoRR (2022)
Ningyuan Teresa Huang, David W. Hogg, Soledad Villar
Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions. SIAM J. Math. Data Sci. 4 (1) (2022)
Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
Scalars are universal: Equivariant machine learning, structured like classical physics. NeurIPS (2021)
Weichi Yao, Kate Storey-Fisher, David W. Hogg, Soledad Villar
A simple equivariant machine learning method for dynamics based on scalars. CoRR (2021)
Soledad Villar, David W. Hogg, Kate Storey-Fisher, Weichi Yao, Ben Blum-Smith
Scalars are universal: Gauge-equivariant machine learning, structured like classical physics. CoRR (2021)
David W. Hogg, Soledad Villar
Fitting very flexible models: Linear regression with large numbers of parameters. CoRR (2021)
Ningyuan Teresa Huang, Soledad Villar
A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants. ICASSP (2021)
Andrew J. Blumberg, Mathieu Carrière, Michael A. Mandell, Raul Rabadan, Soledad Villar
MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data. CoRR (2020)
Culver McWhirter, Dustin G. Mixon, Soledad Villar
SqueezeFit: Label-Aware Dimensionality Reduction by Semidefinite Programming. IEEE Trans. Inf. Theory 66 (6) (2020)
Ningyuan Huang, David W. Hogg, Soledad Villar
Dimensionality reduction, regularization, and generalization in overparameterized regressions. CoRR (2020)
Efe Onaran, Soledad Villar
Efficient Belief Propagation for Graph Matching. ICASSP (2020)
Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna
Can graph neural networks count substructures? CoRR (2020)
Zhengdao Chen, Lei Chen, Soledad Villar, Joan Bruna
Can Graph Neural Networks Count Substructures? NeurIPS (2020)
Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna
On the equivalence between graph isomorphism testing and function approximation with GNNs. CoRR (2019)
Weichi Yao, Afonso S. Bandeira, Soledad Villar
Experimental performance of graph neural networks on random instances of max-cut. CoRR (2019)
Zhengdao Chen, Soledad Villar, Lei Chen, Joan Bruna
On the equivalence between graph isomorphism testing and function approximation with GNNs. NeurIPS (2019)
Richard Kueng, Dustin G. Mixon, Soledad Villar
Fair redistricting is hard. Theor. Comput. Sci. 791 (2019)
Richard Kueng, Dustin G. Mixon, Soledad Villar
Fair redistricting is hard. CoRR (2018)
Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna
Revised Note on Learning Quadratic Assignment with Graph Neural Networks. DSW (2018)
Dustin G. Mixon, Soledad Villar
SUNLayer: Stable denoising with generative networks. CoRR (2018)
Culver McWhirter, Dustin G. Mixon, Soledad Villar
SqueezeFit: Label-aware dimensionality reduction by semidefinite programming. CoRR (2018)
Dustin G. Mixon, Soledad Villar
Utility Ghost: Gamified redistricting with partisan symmetry. CoRR (2018)
Alex Nowak, Soledad Villar, Afonso S. Bandeira, Joan Bruna
A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks. CoRR (2017)
Takayuki Iguchi, Dustin G. Mixon, Jesse Peterson, Soledad Villar
Probably certifiably correct k-means clustering. Math. Program. 165 (2) (2017)
Efe Onaran, Soledad Villar
Projected Power Iteration for Network Alignment. CoRR (2017)
Soledad Villar, Afonso S. Bandeira, Andrew J. Blumberg, Rachel Ward
A polynomial-time relaxation of the Gromov-Hausdorff distance. CoRR (2016)
Dustin G. Mixon, Soledad Villar, Rachel Ward
Clustering subgaussian mixtures with k-means. ITW (2016)
Dustin G. Mixon, Soledad Villar, Rachel Ward
Clustering subgaussian mixtures by semidefinite programming. CoRR (2016)
Takayuki Iguchi, Dustin G. Mixon, Jesse Peterson, Soledad Villar
Probably certifiably correct k-means clustering. CoRR (2015)
Takayuki Iguchi, Dustin G. Mixon, Jesse Peterson, Soledad Villar
On the tightness of an SDP relaxation of k-means. CoRR (2015)
Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward
Relax, No Need to Round: Integrality of Clustering Formulations. ITCS (2015)
Pranjal Awasthi, Afonso S. Bandeira, Moses Charikar, Ravishankar Krishnaswamy, Soledad Villar, Rachel Ward
Relax, no need to round: integrality of clustering formulations. CoRR (2014)