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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Theory
4,950 papers
Papers per year
2000: 1
2001: 2
2002: 3
2003: 3
2004: 9
2005: 4
2006: 32
2007: 25
2008: 31
2009: 25
2010: 37
2011: 37
2012: 45
2013: 76
2014: 66
2015: 72
2016: 102
2017: 156
2018: 246
2019: 353
2020: 447
2021: 567
2022: 646
2023: 741
2024: 670
2025: 426
2026: 128
Papers
Defects of Convolutional Decoder Networks in Frequency Representation
ICML 2023
Survival Instinct in Offline Reinforcement Learning
NIPS 2023
Benchmarking Rigid Body Contact Models
L4DC 2023
Can We Find Strong Lottery Tickets in Generative Models?
AAAI 2023
Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds
NIPS 2023
The Numerical Stability of Hyperbolic Representation Learning
ICML 2023
On the spectral bias of two-layer linear networks
NIPS 2023
A Unified View of Evaluation Metrics for Structured Prediction
EMNLP 2023
An Experimental Comparison of Multiwinner Voting Rules on Approval Elections
IJCAI 2023
A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective
NIPS 2023
Understanding, Predicting and Better Resolving Q-Value Divergence in Offline-RL
NIPS 2023
Statistical Analysis of Quantum State Learning Process in Quantum Neural Networks
NIPS 2023
Improved Kernel Alignment Regret Bound for Online Kernel Learning
AAAI 2023
Complexity of Safety and coSafety Fragments of Linear Temporal Logic
AAAI 2023
PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization
NIPS 2023
AMDP: An Adaptive Detection Procedure for False Discovery Rate Control in High-Dimensional Mediation Analysis
NIPS 2023
On the Limitations of Simulating Active Learning
ACL 2023
A Randomized Approach to Tight Privacy Accounting
NIPS 2023
Comprehensive Algorithm Portfolio Evaluation using Item Response Theory
JMLR 2023
Structural generalization in COGS: Supertagging is (almost) all you need
EMNLP 2023
A Theoretical Analysis of Optimistic Proximal Policy Optimization in Linear Markov Decision Processes
NIPS 2023
Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes
ICML 2023
On the Convergence of SARSA with Linear Function Approximation
ICML 2023
Transformers are uninterpretable with myopic methods: a case study with bounded Dyck grammars
NIPS 2023
On the Variance, Admissibility, and Stability of Empirical Risk Minimization
NIPS 2023
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