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Conference on Learning Theory

COLT

A*

CORE rank

CORE rank (raw)

A*

Fields of research

Machine Learning · Artificial Intelligence

Papers indexed

2,661

1988–2026

Papers per year

1988197 peak2026

COLT papers

2,661 records sourced from DBLP. Search titles, filter by year, sort by recency.

YearTitleAuthors
2023Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation.Qiwen Cui, Kaiqing Zhang, Simon S. Du
2023Open Problem: Polynomial linearly-convergent method for g-convex optimization?Christopher Criscitiello, David Martnez-Rubio, Nicolas Boumal
2023Curvature and complexity: Better lower bounds for geodesically convex optimization.Christopher Criscitiello, Nicolas Boumal
2023Open problem: log(n) factor in "Local Glivenko-Cantelli.Doron Cohen, Aryeh Kontorovich
2023Local Glivenko-Cantelli.Doron Cohen, Aryeh Kontorovich
2023Bregman Deviations of Generic Exponential Families.Sayak Ray Chowdhury, Patrick Saux, Odalric Maillard, Aditya Gopalan
2023Learning Narrow One-Hidden-Layer ReLU Networks.Sitan Chen, Zehao Dou, Surbhi Goel, Adam R. Klivans, Raghu Meka
2023Fast Algorithms for a New Relaxation of Optimal Transport.Moses Charikar, Beidi Chen, Christopher R, Erik Waingarten
2023Open Problem: Is There a First-Order Method that Only Converges to Local Minimax Optima?Jiseok Chae, Kyuwon Kim, Donghwan Kim
2023Repeated Bilateral Trade Against a Smoothed Adversary.Nicol Cesa-Bianchi, Tommaso Renato Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi
2023The Implicit Bias of Batch Normalization in Linear Models and Two-layer Linear Convolutional Neural Networks.Yuan Cao, Difan Zou, Yuanzhi Li, Quanquan Gu
2023Beyond Parallel Pancakes: Quasi-Polynomial Time Guarantees for Non-Spherical Gaussian Mixtures.Rares-Darius Buhai, David Steurer
2023Geodesically convex M-estimation in metric spaces.Victor-Emmanuel Brunel
2023Improper Multiclass Boosting.Nataly Brukhim, Steve Hanneke, Shay Moran
2023Fast, Sample-Efficient, Affine-Invariant Private Mean and Covariance Estimation for Subgaussian Distributions.Gavin Brown, Samuel B. Hopkins, Adam Smith
2023Detection-Recovery and Detection-Refutation Gaps via Reductions from Planted Clique.Guy Bresler, Tianze Jiang
2023Fine-Grained Distribution-Dependent Learning Curves.Olivier Bousquet, Steve Hanneke, Shay Moran, Jonathan Shafer, Ilya O. Tolstikhin
2023Precise Asymptotic Analysis of Deep Random Feature Models.David Bosch, Ashkan Panahi, Babak Hassibi
2023Oracle-Efficient Smoothed Online Learning for Piecewise Continuous Decision Making.Adam Block, Max Simchowitz, Alexander Rakhlin
2023The Sample Complexity of Approximate Rejection Sampling With Applications to Smoothed Online Learning.Adam Block, Yury Polyanskiy
2023Quadratic Memory is Necessary for Optimal Query Complexity in Convex Optimization: Center-of-Mass is Pareto-Optimal.Mose Blanchard, Junhui Zhang, Patrick Jaillet
2023Complexity of High-Dimensional Identity Testing with Coordinate Conditional Sampling.Antonio Blanca, Zongchen Chen, Daniel Stefankovic, Eric Vigoda
2023Minimax Instrumental Variable Regression and LAndrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023Inference on Strongly Identified Functionals of Weakly Identified Functions.Andrew Bennett, Nathan Kallus, Xiaojie Mao, Whitney Newey, Vasilis Syrgkanis, Masatoshi Uehara
2023Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap.Raef Bassily, Cristbal Guzmn, Michael Menart
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