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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

Best Artificial Intelligence conferencesBest Machine Learning conferences

Papers per year

1988197 peak2026

Most published authors

COLT papers

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

YearTitleAuthors
2026Truly Adapting to Adversarial Constraints in Constrained MABs.Francesco Emanuele Stradi, Kalana Kalupahana, Matteo Castiglioni, Alberto Marchesi, Nicola Gatti
2026Privately Estimating Black-Box Statistics.Gnter F. Steinke, Thomas Steinke
2026Revisiting the (Sub)Optimality of Best-of-N for Inference-Time Alignment.Ved Sriraman, Adam Block
2026Efficient Learning and Symmetry Discovery under Exact Invariances.Ashkan Soleymani, Behrooz Tahmasebi, Patrick Jaillet, Stefanie Jegelka
2026Finite Sample Bounds for Learning with Score Matching.Devin Smedira, Abhijith Jayakumar, Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
2026Testing for a Hidden Geometry in Random Graphs.Amit Silber, Mor Oren-Loberman, Wasim Huleihel
2026Optimal Sample Complexity Lower Bounds on Conditional Independence Testing.Jan Seyfried, Neelkanth Mishra, Sayantan Sen, Marco Tomamichel
2026The Hidden Cost of Approximation in Online Mirror Descent.Ofir Schlisselberg, Uri Sherman, Tomer Koren, Yishay Mansour
2026Convergence of Continual Learning in Homogeneous Deep Networks.Matan Schliserman, Gon Buzaglo, Itay Evron, Daniel Soudry
2026A Depth Hierarchy for Computing the Maximum in ReLU Networks via Extremal Graph Theory.Itay Safran
2026Private Linear Regression via a Down-Sensitivity to Privacy Reduction.Ittai Rubinstein, Chris Ge, Samuel B. Hopkins
2026Continuous time policy evaluation is easier with noisy dynamics.Samuel Robertson, Thomas Newton, Csaba Szepesvri
2026Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining.Yunwei Ren, Yatin Dandi, Florent Krzakala, Jason D. Lee
2026Learning to Reason with Curriculum I: Provable Benefits of Autocurriculum.Nived Rajaraman, Audrey Huang, Miro Dudk, Robert E. Schapire, Dylan J. Foster, Akshay Krishnamurthy
2026Near-Optimal Regret for Distributed Adversarial Bandits: A Black-Box Approach.Hao Qiu, Mengxiao Zhang, Nicol Cesa-Bianchi
2026Taming the Monster Every Context: Complexity Measure and Unified Framework for Offline-Oracle Efficient Contextual Bandits.Hao Qin, Chicheng Zhang
2026Deep Q-Learning on Hlder Spaces.Qian Qi
2026Boosting with List-Decodable Codes.Addison Prairie, Li-Yang Tan
2026Spectral Recovery of a Planted Triangle-Dense Subgraph.Sam van der Poel, Cheng Mao, Benjamin McKenna
2026An Exponential Lower Bound for Spectral Density Estimation on Unweighted Graphs.Pan Peng, Yuyang Wang, Joy Qiping Yang, Yichun Yang
2026Equivalence of Coarse and Fine-Grained Models for Learning with Distribution Shift.Shyamal Patel, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
2026Invited Open Problem: Does Differential Privacy Make PAC Learning Much Harder?Kobbi Nissim, Uri Stemmer, Eliad Tsfadia
2026Graph neural networks extrapolate out-of-distribution for shortest paths.Robert R. Nerem, Samantha Chen, Sanjoy Dasgupta, Yusu Wang
2026Optimal Neural Network Approximation of Smooth Compositional Functions on Sets with Low Intrinsic Dimension.Thomas Nagler, Sophie Langer
2026Minimax Limits of k-Fold Cross-Validation via Majority.Ido Nachum, Rdiger L. Urbanke, Thomas Weinberger
26–50 of 2,661← PreviousNext →

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