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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Learning Theory
5,312 papers
Papers per year
2001: 1
2002: 16
2003: 16
2004: 15
2005: 17
2006: 30
2007: 32
2008: 32
2009: 34
2010: 66
2011: 76
2012: 74
2013: 94
2014: 115
2015: 123
2016: 128
2017: 185
2018: 219
2019: 390
2020: 466
2021: 640
2022: 664
2023: 799
2024: 688
2025: 307
2026: 85
Papers
Model-Free Reinforcement Learning with the Decision-Estimation Coefficient
NIPS 2023
Adaptive Data Analysis in a Balanced Adversarial Model
NIPS 2023
Spuriosity Didn’t Kill the Classifier: Using Invariant Predictions to Harness Spurious Features
NIPS 2023
Counterfactual Evaluation of Peer-Review Assignment Policies
NIPS 2023
Online Learning in Dynamically Changing Environments
COLT 2023
A Needle in a Haystack: An Analysis of High-Agreement Workers on MTurk for Summarization
ACL 2023
Learning and Testing Latent-Tree Ising Models Efficiently
COLT 2023
SQ Lower Bounds for Learning Mixtures of Separated and Bounded Covariance Gaussians
COLT 2023
Limitations on approximation by deep and shallow neural networks
JMLR 2023
On the Generalization Properties of Diffusion Models
NIPS 2023
Regret-Optimal Model-Free Reinforcement Learning for Discounted MDPs with Short Burn-In Time
NIPS 2023
Random Feature Amplification: Feature Learning and Generalization in Neural Networks
JMLR 2023
Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis.
UAI 2023
Regret Minimization via Saddle Point Optimization
NIPS 2023
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training
NIPS 2023
Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
NIPS 2023
Autonomous Exploration for Navigating in MDPs Using Blackbox RL Algorithms
IJCAI 2023
Multiclass Boosting: Simple and Intuitive Weak Learning Criteria
NIPS 2023
Performance Bounds for Policy-Based Average Reward Reinforcement Learning Algorithms
NIPS 2023
The Influence of Dimensions on the Complexity of Computing Decision Trees
AAAI 2023
Statistical and Computational Limits for Tensor-on-Tensor Association Detection
COLT 2023
Adversarially Robust Learning with Tolerance
ALT 2023
Optimize Planning Heuristics to Rank, not to Estimate Cost-to-Goal
NIPS 2023
“No Free Lunch” in Neural Architectures? A Joint Analysis of Expressivity, Convergence, and Generalization
AUTOML 2023
A Blackbox Approach to Best of Both Worlds in Bandits and Beyond
COLT 2023
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