Frederic Koehler

Most-cited papers

A spectral condition for spectral gap: fast mixing in high-temperature Ising models
Ronen Eldan, Frederic Koehler, O. Zeitouni
2020Probability theory and related fields110 citations Open access
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Statistical Efficiency of Score Matching: The View from Isoperimetry
Frederic Koehler, Alexander Heckett, Andrej Risteski
2022International Conference on Learning Representations84 citations Open access
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Entropic independence: optimal mixing of down-up random walks
Nima Anari, Vishesh Jain, Frederic Koehler, H. Pham +1 more
2022Symposium on the Theory of Computing75 citations
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Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications
Linus Hamilton, Frederic Koehler, Ankur Moitra
2017Neural Information Processing Systems68 citations
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Uniform Convergence of Interpolators: Gaussian Width, Norm Bounds, and Benign Overfitting
Frederic Koehler, Lijia Zhou, Danica J. Sutherland, N. Srebro
2021Neural Information Processing Systems66 citations
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Mean-field approximation, convex hierarchies, and the optimality of correlation rounding: a unified perspective
Vishesh Jain, Frederic Koehler, Andrej Risteski
2018Symposium on the Theory of Computing43 citations Open access
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Online and Distribution-Free Robustness: Regression and Contextual Bandits with Huber Contamination
Si-Tan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2020IEEE Annual Symposium on Foundations of Computer Science39 citations Open access
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Learning Some Popular Gaussian Graphical Models without Condition Number Bounds
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Ankur Moitra
2019Neural Information Processing Systems38 citations
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The Mean-Field Approximation: Information Inequalities, Algorithms, and Complexity
Vishesh Jain, Frederic Koehler, Elchanan Mossel
2018Annual Conference Computational Learning Theory34 citations
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Trickle-Down in Localization Schemes and Applications
Nima Anari, Frederic Koehler, T. Vuong
2024Symposium on the Theory of Computing33 citations
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Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
2020International Conference on Machine Learning33 citations
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Learning restricted Boltzmann machines via influence maximization
Guy Bresler, Frederic Koehler, Ankur Moitra, Elchanan Mossel
2018Symposium on the Theory of Computing31 citations Open access
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Sampling Approximately Low-Rank Ising Models: MCMC meets Variational Methods
Frederic Koehler, Holden Lee, Andrej Risteski
2022Annual Conference Computational Learning Theory30 citations
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Entropic Independence II: Optimal Sampling and Concentration via Restricted Modified Log-Sobolev Inequalities
Nima Anari, Vishesh Jain, Frederic Koehler, H. Pham +1 more
2021arXiv.org30 citations
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Optimistic Rates: A Unifying Theory for Interpolation Learning and Regularization in Linear Regression
Lijia Zhou, Frederic Koehler, Danica J. Sutherland, N. Srebro
2021ACM / IMS Journal of Data Science30 citations Open access
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Provable Algorithms for Inference in Topic Models
Sanjeev Arora, Rong Ge, Frederic Koehler, Tengyu Ma +1 more
2016International Conference on Machine Learning30 citations
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Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability
Si-Tan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2020Neural Information Processing Systems28 citations
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Universality of Spectral Independence with Applications to Fast Mixing in Spin Glasses
Nima Anari, Vishesh Jain, Frederic Koehler, H. Pham +1 more
2023ACM-SIAM Symposium on Discrete Algorithms24 citations Open access
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Optimal Batch Schedules for Parallel Machines
Frederic Koehler, S. Khuller
2013Workshop on Algorithms and Data Structures24 citations
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Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Connections to Evolvability
Si-Tan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2020arXiv.org23 citations
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On the Power of Preconditioning in Sparse Linear Regression
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2021IEEE Annual Symposium on Foundations of Computer Science20 citations Open access
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Entropic Independence in High-Dimensional Expanders: Modified Log-Sobolev Inequalities for Fractionally Log-Concave Polynomials and the Ising Model
Nima Anari, Vishesh Jain, Frederic Koehler, H. Pham +1 more
2021arXiv.org20 citations
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Entropic Independence I: Modified Log-Sobolev Inequalities for Fractionally Log-Concave Distributions and High-Temperature Ising Models
Nima Anari, Vishesh Jain, Frederic Koehler, H. Pham +1 more
202119 citations
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How Many Subpopulations Is Too Many? Exponential Lower Bounds for Inferring Population Histories
Younhun Kim, Frederic Koehler, Ankur Moitra, Elchanan Mossel +1 more
2018Annual International Conference on Research in Computational Molecular Biology18 citations Open access
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Stein's unbiased risk estimate and Hyv\"arinen's score matching
S. Ghosh, N. Ignatiadis, Frederic Koehler, Amber Lee
202517 citations
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Multidimensional Scaling: Approximation and Complexity
E. Demaine, Adam Hesterberg, Frederic Koehler, J. Lynch +1 more
2021International Conference on Machine Learning17 citations
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Busy Time Scheduling on a Bounded Number of Machines (Extended Abstract)
Frederic Koehler, S. Khuller
2017Workshop on Algorithms and Data Structures16 citations
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Efficiently learning and sampling multimodal distributions with data-based initialization
Frederic Koehler, Holden Lee, T. Vuong
2024arXiv.org15 citations
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Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias
Frederic Koehler, Viraj Mehta, Andrej Risteski, Chenghui Zhou
2021International Conference on Learning Representations15 citations
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Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay
Frederic Koehler
2019Neural Information Processing Systems15 citations
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A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou, Frederic Koehler, P. Sur, Danica J. Sutherland +1 more
2022Neural Information Processing Systems13 citations Open access
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Reconstruction on Trees and Low-Degree Polynomials
Frederic Koehler, Elchanan Mossel
2021Neural Information Processing Systems13 citations Open access
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Representational Power of ReLU Networks and Polynomial Kernels: Beyond Worst-Case Analysis
Frederic Koehler, Andrej Risteski
2018arXiv.org12 citations
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Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
Frederic Koehler, T. Vuong
2023International Conference on Learning Representations11 citations Open access
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Kalman filtering with adversarial corruptions
Si-Tan Chen, Frederic Koehler, Ankur Moitra, Morris Yau
2021Symposium on the Theory of Computing11 citations Open access
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Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
Enric Boix-Adserà, Guy Bresler, Frederic Koehler
2021IEEE Annual Symposium on Foundations of Computer Science11 citations Open access
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Feature Adaptation for Sparse Linear Regression
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2023Neural Information Processing Systems10 citations Open access
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Parallel Sampling via Autospeculation
Nima Anari, Carlo Baronio, C.-J. Chen, Alireza Haqi +3 more
2025Symposium on the Theory of Computing8 citations Open access
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From Boltzmann Machines to Neural Networks and Back Again
Surbhi Goel, Adam R. Klivans, Frederic Koehler
2020Neural Information Processing Systems7 citations
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Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation
Vishesh Jain, Frederic Koehler, Jingbo Liu, Elchanan Mossel
2019Annual Conference Computational Learning Theory6 citations
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Approximating Partition Functions in Constant Time
Vishesh Jain, Frederic Koehler, Elchanan Mossel
2017arXiv.org6 citations
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Constructive Approximation under Carleman's Condition, with Applications to Smoothed Analysis
Frederic Koehler, Bei-Ning Wu
2025arXiv.org5 citations
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Lasso with Latents: Efficient Estimation, Covariate Rescaling, and Computational-Statistical Gaps
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2024Annual Conference Computational Learning Theory5 citations
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Lower Bounds on Randomly Preconditioned Lasso via Robust Sparse Designs
Jonathan A. Kelner, Frederic Koehler, Raghu Meka, Dhruv Rohatgi
2022Neural Information Processing Systems5 citations
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Anticoncentration of the Permanent in Ginibre Ensembles
Frederic Koehler, Pui-Kuen Leung
2026arXiv.org4 citations
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Approximating the Permanent of a Random Matrix with Polynomially Small Mean: Zeros and Universality
Frederic Koehler, Pui-Kuen Leung
2026arXiv.org4 citations
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Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting
Serina Chang, Frederic Koehler, Zhaonan Qu, J. Leskovec +1 more
2024International Conference on Machine Learning4 citations
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The Comparative Power of ReLU Networks and Polynomial Kernels in the Presence of Sparse Latent Structure
Frederic Koehler, Andrej Risteski
2018International Conference on Learning Representations4 citations
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The Vertex Sample Complexity of Free Energy is Polynomial
Vishesh Jain, Frederic Koehler, Elchanan Mossel
2018Annual Conference Computational Learning Theory4 citations
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Uniform Convergence with Square-Root Lipschitz Loss
Lijia Zhou, Zhen Dai, Frederic Koehler, N. Srebro
2023Neural Information Processing Systems2 citations Open access
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