Soledad Villar

CoRR, 2024

Learning functions on symmetric matrices and point clouds via lightweight invariant features.

[BibT_eX]

[DOI]

CoRR, 2024

Position: Is machine learning good or bad for the natural sciences?

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs.

[BibT_eX]

[DOI]

Luana Ruiz

Ningyuan Teresa Huang

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Dimensionless machine learning: Imposing exact units equivariance.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2023

GeometricImageNet: Extending convolutional neural networks to vector and tensor images.

[BibT_eX]

[DOI]

CoRR, 2023

The passive symmetries of machine learning.

[BibT_eX]

[DOI]

CoRR, 2023

Approximately Equivariant Graph Networks.

[BibT_eX]

[DOI]

Ningyuan Huang

Ron Levie

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fine-grained Expressivity of Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Second Learning on Graphs Conference: Preface.

[BibT_eX]

[DOI]

Benjamin Paul Chamberlain

Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Prospective Learning: Principled Extrapolation to the Future.

[BibT_eX]

[DOI]

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions.

[BibT_eX]

[DOI]

Ningyuan Teresa Huang

SIAM J. Math. Data Sci., 2022

Sketch-and-solve approaches to k-means clustering by semidefinite programming.

[BibT_eX]

[DOI]

CoRR, 2022

Graph Neural Networks for Community Detection on Sparse Graphs.

[BibT_eX]

[DOI]

Luana Ruiz

Ningyuan Huang

CoRR, 2022

Deep Learning is Provably Robust to Symmetric Label Noise.

[BibT_eX]

[DOI]

CoRR, 2022

Shuffled linear regression through graduated convex relaxation.

[BibT_eX]

[DOI]

Efe Onaran

CoRR, 2022

Equivariant maps from invariant functions.

[BibT_eX]

[DOI]

Ben Blum-Smith

CoRR, 2022

From Local to Global: Spectral-Inspired Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2022

MarkerMap: nonlinear marker selection for single-cell studies.

[BibT_eX]

[DOI]

CoRR, 2022

2021

A simple equivariant machine learning method for dynamics based on scalars.

[BibT_eX]

[DOI]

CoRR, 2021

Scalars are universal: Gauge-equivariant machine learning, structured like classical physics.

[BibT_eX]

[DOI]

CoRR, 2021

Fitting very flexible models: Linear regression with large numbers of parameters.

[BibT_eX]

[DOI]

CoRR, 2021

Scalars are universal: Equivariant machine learning, structured like classical physics.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants.

[BibT_eX]

[DOI]

Ningyuan Teresa Huang

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

SqueezeFit: Label-Aware Dimensionality Reduction by Semidefinite Programming.

[BibT_eX]

[DOI]

Culver McWhirter

IEEE Trans. Inf. Theory, 2020

MREC: a fast and versatile framework for aligning and matching point clouds with applications to single cell molecular data.

[BibT_eX]

[DOI]

CoRR, 2020

Can Graph Neural Networks Count Substructures?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Belief Propagation for Graph Matching.

[BibT_eX]

[DOI]

Efe Onaran

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Fair redistricting is hard.

[BibT_eX]

[DOI]

Richard Kueng

Theor. Comput. Sci., 2019

Experimental performance of graph neural networks on random instances of max-cut.

[BibT_eX]

[DOI]

Weichi Yao

Afonso S. Bandeira

CoRR, 2019

On the equivalence between graph isomorphism testing and function approximation with GNNs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Utility Ghost: Gamified redistricting with partisan symmetry.

[BibT_eX]

[DOI]

CoRR, 2018

SUNLayer: Stable denoising with generative networks.

[BibT_eX]

[DOI]

CoRR, 2018

Revised Note on Learning Quadratic Assignment with Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Data Science Workshop, 2018

2017

Probably certifiably correct k-means clustering.

[BibT_eX]

[DOI]

Math. Program., 2017

Projected Power Iteration for Network Alignment.

[BibT_eX]

[DOI]

Efe Onaran

CoRR, 2017

A Note on Learning Algorithms for Quadratic Assignment with Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2017

2016

A polynomial-time relaxation of the Gromov-Hausdorff distance.

[BibT_eX]

[DOI]

CoRR, 2016

Clustering subgaussian mixtures by semidefinite programming.

[BibT_eX]

[DOI]

Rachel A. Ward

CoRR, 2016

Clustering subgaussian mixtures with k-means.

[BibT_eX]

[DOI]

Rachel A. Ward

Proceedings of the 2016 IEEE Information Theory Workshop, 2016

2015

On the tightness of an SDP relaxation of k-means.

[BibT_eX]

[DOI]

CoRR, 2015

Relax, No Need to Round: Integrality of Clustering Formulations.

[BibT_eX]

[DOI]

Pranjal Awasthi

Afonso S. Bandeira

Moses Charikar

Ravishankar Krishnaswamy