Jonathan Niles-Weed

56 papers A* 20A 1Journal 35
YearRankTypeTitle / Venue / Authors
2026 J jnl
Reweighted information inequalities.
CoRR
Jonathan Niles-Weed
2025 J jnl
A Bayesian Proof of the Spread Lemma.
Random Struct. Algorithms
Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik
2025 J jnl
Besting Good-Turing: Optimality of Non-Parametric Maximum Likelihood for Distribution Estimation.
CoRR
Yanjun Han, Jonathan Niles-Weed, Yandi Shen, Yihong Wu
2025 A conf
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps.
AISTATS
Ricardo Baptista, Aram-Alexandre Pooladian, Michael Brennan, Youssef Marzouk, Jonathan Niles-Weed
2025 J jnl
Plug-in Estimation of Schrödinger Bridges.
SIAM J. Math. Data Sci.
Aram-Alexandre Pooladian, Jonathan Niles-Weed
2025 J jnl
The multirank likelihood for semiparametric canonical correlation analysis.
J. Multivar. Anal.
Jordan Bryan, Jonathan Niles-Weed, Peter D. Hoff
2025 A* conf
Trajectory Inference with Smooth Schrödinger Bridges.
ICML
Wanli Hong, Yuliang Shi, Jonathan Niles-Weed
2025 J jnl
Trajectory Inference with Smooth Schrödinger Bridges.
CoRR
Wanli Hong, Yuliang Shi, Jonathan Niles-Weed
2024 J jnl
Approximate independence of permutation mixtures.
CoRR
Yanjun Han, Jonathan Niles-Weed
2024 J jnl
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps.
CoRR
Ricardo Baptista, Aram-Alexandre Pooladian, Michael Brennan, Youssef M. Marzouk, Jonathan Niles-Weed
2024 J jnl
Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias.
CoRR
Yifan Chen, Xiaoou Cheng, Jonathan Niles-Weed, Jonathan Weare
2024 J jnl
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification.
J. Mach. Learn. Res.
Natalie S. Frank, Jonathan Niles-Weed
2024 A* conf
Learning Elastic Costs to Shape Monge Displacements.
NeurIPS
Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi
2024 J jnl
Learning large softmax mixtures with warm start EM.
CoRR
Xin Bing, Florentina Bunea, Jonathan Niles-Weed, Marten H. Wegkamp
2024 J jnl
Plug-in estimation of Schrödinger bridges.
CoRR
Aram-Alexandre Pooladian, Jonathan Niles-Weed
2024 A* conf
Progressive Entropic Optimal Transport Solvers.
NeurIPS
Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi
2024 J jnl
Progressive Entropic Optimal Transport Solvers.
CoRR
Parnian Kassraie, Aram-Alexandre Pooladian, Michal Klein, James Thornton, Jonathan Niles-Weed, Marco Cuturi
2023 J jnl
An Improved Central Limit Theorem and Fast Convergence Rates for Entropic Transportation Costs.
SIAM J. Math. Data Sci.
Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed
2023 A* conf
Asymptotic confidence sets for random linear programs.
COLT
Shuyu Liu, Florentina Bunea, Jonathan Niles-Weed
2023 J jnl
It Was "All" for "Nothing": Sharp Phase Transitions for Noiseless Discrete Channels.
IEEE Trans. Inf. Theory
Jonathan Niles-Weed, Ilias Zadik
2023 J jnl
Learning Costs for Structured Monge Displacements.
CoRR
Michal Klein, Aram-Alexandre Pooladian, Pierre Ablin, Eugène Ndiaye, Jonathan Niles-Weed, Marco Cuturi
2023 A* conf
Minimax estimation of discontinuous optimal transport maps: The semi-discrete case.
ICML
Aram-Alexandre Pooladian, Vincent Divol, Jonathan Niles-Weed
2023 A* conf
Perturbation Analysis of Neural Collapse.
ICML
Tom Tirer, Haoxiang Huang, Jonathan Niles-Weed
2023 A* conf
Sharp thresholds in inference of planted subgraphs.
COLT
Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik
2023 J jnl
Sharp thresholds in inference of planted subgraphs.
CoRR
Elchanan Mossel, Jonathan Niles-Weed, Youngtak Sohn, Nike Sun, Ilias Zadik
2023 A* conf
The Adversarial Consistency of Surrogate Risks for Binary Classification.
NeurIPS
Natalie Frank, Jonathan Niles-Weed
2023 J jnl
The Adversarial Consistency of Surrogate Risks for Binary Classification.
CoRR
Natalie Frank, Jonathan Niles-Weed
2022 J jnl
A second moment proof of the spread lemma.
CoRR
Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik
2022 J jnl
An improved central limit theorem and fast convergence rates for entropic transportation costs.
CoRR
Eustasio del Barrio, Alberto González-Sanz, Jean-Michel Loubes, Jonathan Niles-Weed
2022 J jnl
Asymptotics for Semidiscrete Entropic Optimal Transport.
SIAM J. Math. Anal.
Jason M. Altschuler, Jonathan Niles-Weed, Austin J. Stromme
2022 A* conf
Asymptotics of smoothed Wasserstein distances in the small noise regime.
NeurIPS
Yunzi Ding, Jonathan Niles-Weed
2022 A* conf
Debiaser Beware: Pitfalls of Centering Regularized Transport Maps.
ICML
Aram-Alexandre Pooladian, Marco Cuturi, Jonathan Niles-Weed
2022 A* conf
Deep Probability Estimation.
ICML
Sheng Liu, Aakash Kaku, Weicheng Zhu, Matan Leibovich, Sreyas Mohan, Boyang Yu, Haoxiang Huang, Laure Zanna, Narges Razavian, Jonathan Niles-Weed, Carlos Fernandez-Granda
2022 A* conf
Distributional Convergence of the Sliced Wasserstein Process.
NeurIPS
Jiaqi Xi, Jonathan Niles-Weed
2022 J jnl
Existence and Minimax Theorems for Adversarial Surrogate Risks in Binary Classification.
CoRR
Natalie S. Frank, Jonathan Niles-Weed
2022 J jnl
Matrix Concentration for Products.
Found. Comput. Math.
De Huang, Jonathan Niles-Weed, Joel A. Tropp, Rachel A. Ward
2022 J jnl
On the Second Kahn-Kalai Conjecture.
CoRR
Elchanan Mossel, Jonathan Niles-Weed, Nike Sun, Ilias Zadik
2022 J jnl
Perturbation Analysis of Neural Collapse.
CoRR
Tom Tirer, Haoxiang Huang, Jonathan Niles-Weed
2022 A* conf
Strong recovery of geometric planted matchings.
SODA
Dmitriy Kunisky, Jonathan Niles-Weed
2022 J jnl
The discrepancy of random rectangular matrices.
Random Struct. Algorithms
Dylan J. Altschuler, Jonathan Niles-Weed
2021 A* conf
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels.
COLT
Jonathan Niles-Weed, Ilias Zadik
2021 J jnl
It was "all" for "nothing": sharp phase transitions for noiseless discrete channels.
CoRR
Jonathan Niles-Weed, Ilias Zadik
2021 A* conf
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates.
COLT
De Huang, Jonathan Niles-Weed, Rachel A. Ward
2021 J jnl
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates.
CoRR
De Huang, Jonathan Niles-Weed, Rachel A. Ward
2021 J jnl
Strong recovery of geometric planted matchings.
CoRR
Dmitriy Kunisky, Jonathan Niles-Weed
2021 J jnl
The Discrepancy of Random Rectangular Matrices.
CoRR
Dylan J. Altschuler, Jonathan Niles-Weed
2020 J jnl
Convergence of Smoothed Empirical Measures With Applications to Entropy Estimation.
IEEE Trans. Inf. Theory
Ziv Goldfeld, Kristjan H. Greenewald, Jonathan Niles-Weed, Yury Polyanskiy
2020 A* conf
Early-Learning Regularization Prevents Memorization of Noisy Labels.
NeurIPS
Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda
2020 J jnl
Early-Learning Regularization Prevents Memorization of Noisy Labels.
CoRR
Sheng Liu, Jonathan Niles-Weed, Narges Razavian, Carlos Fernandez-Granda
2020 J jnl
Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport.
CoRR
Gonzalo E. Mena, Amin Nejatbakhsh, Erdem Varol, Jonathan Niles-Weed
2020 A* conf
Supervised Quantile Normalization for Low Rank Matrix Factorization.
ICML
Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert
2020 J jnl
Supervised Quantile Normalization for Low-rank Matrix Approximation.
CoRR
Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, Jean-Philippe Vert
2020 A* conf
The All-or-Nothing Phenomenon in Sparse Tensor PCA.
NeurIPS
Jonathan Niles-Weed, Ilias Zadik
2020 J jnl
The All-or-Nothing Phenomenon in Sparse Tensor PCA.
CoRR
Jonathan Niles-Weed, Ilias Zadik
2019 A* conf
Massively scalable Sinkhorn distances via the Nyström method.
NeurIPS
Jason M. Altschuler, Francis R. Bach, Alessandro Rudi, Jonathan Niles-Weed
2019 A* conf
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem.
NeurIPS
Gonzalo Mena, Jonathan Niles-Weed