Frederic Koehler

Thuy-Duong Vuong

CoRR, 2023

Influences in Mixing Measures.

[BibT_eX]

[DOI]

CoRR, 2023

Uniform Convergence with Square-Root Lipschitz Loss.

[BibT_eX]

[DOI]

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

Feature Adaptation for Sparse Linear Regression.

[BibT_eX]

[DOI]

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

Statistical Efficiency of Score Matching: The View from Isoperimetry.

[BibT_eX]

[DOI]

Alexander Heckett

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Distributional Hardness Against Preconditioned Lasso via Erasure-Robust Designs.

[BibT_eX]

[DOI]

CoRR, 2022

Kalman filtering with adversarial corruptions.

[BibT_eX]

[DOI]

Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

Entropic independence: optimal mixing of down-up random walks.

[BibT_eX]

[DOI]

Proceedings of the STOC '22: 54th Annual ACM SIGACT Symposium on Theory of Computing, Rome, Italy, June 20, 2022

A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Reconstruction on Trees and Low-Degree Polynomials.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods.

[BibT_eX]

[DOI]

Holden Lee

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression.

[BibT_eX]

[DOI]

CoRR, 2021

Entropic Independence II: Optimal Sampling and Concentration via Restricted Modified Log-Sobolev Inequalities.

[BibT_eX]

[DOI]

CoRR, 2021

Entropic Independence in High-Dimensional Expanders: Modified Log-Sobolev Inequalities for Fractionally Log-Concave Polynomials and the Ising Model.

[BibT_eX]

[DOI]

CoRR, 2021

Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds and Benign Overfitting.

[BibT_eX]

[DOI]

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

Representational aspects of depth and conditioning in normalizing flows.

[BibT_eX]

[DOI]

Viraj Mehta

Proceedings of the 38th International Conference on Machine Learning, 2021

Multidimensional Scaling: Approximation and Complexity.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Power of Preconditioning in Sparse Linear Regression.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination.

[BibT_eX]

[DOI]

Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models.

[BibT_eX]

[DOI]

Enric Boix-Adserà

Guy Bresler

Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

2020

How Many Subpopulations Is Too Many? Exponential Lower Bounds for Inferring Population Histories.

[BibT_eX]

[DOI]

J. Comput. Biol., 2020

Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability.

[BibT_eX]

[DOI]

CoRR, 2020

A Phase Transition in Arrow's Theorem.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Some Popular Gaussian Graphical Models without Condition Number Bounds.

[BibT_eX]

[DOI]

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

From Boltzmann Machines to Neural Networks and Back Again.

[BibT_eX]

[DOI]

Surbhi Goel

Adam R. Klivans

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

Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability.

[BibT_eX]

[DOI]

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

2019

Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective.

[BibT_eX]

[DOI]

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Learning restricted Boltzmann machines via influence maximization.

[BibT_eX]

[DOI]

Guy Bresler

Ankur Moitra

Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019

Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay.

[BibT_eX]

[DOI]

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

The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation.

[BibT_eX]

[DOI]

Proceedings of the Conference on Learning Theory, 2019

2018

Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Restricted Boltzmann Machines via Influence Maximization.

[BibT_eX]

[DOI]

CoRR, 2018

The Vertex Sample Complexity of Free Energy is Polynomial.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity.

[BibT_eX]

[DOI]

Proceedings of the Conference On Learning Theory, 2018

2017

Approximating Partition Functions in Constant Time.

[BibT_eX]

[DOI]

CoRR, 2017

Busy Time Scheduling on a Bounded Number of Machines (Extended Abstract).

[BibT_eX]

[DOI]

Samir Khuller

Proceedings of the Algorithms and Data Structures - 15th International Symposium, 2017

Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications.

[BibT_eX]

[DOI]

Linus Hamilton

Ankur Moitra

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

Provable Algorithms for Inference in Topic Models.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2013

Optimal Batch Schedules for Parallel Machines.

[BibT_eX]

[DOI]