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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
Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization
ICML 2022
Utility Theory for Sequential Decision Making
ICML 2022
Deep Network Approximation in Terms of Intrinsic Parameters
ICML 2022
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
ICML 2022
Coin Flipping Neural Networks
ICML 2022
Reverse Engineering the Neural Tangent Kernel
ICML 2022
Consistent Polyhedral Surrogates for Top-k Classification and Variants
ICML 2022
On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions
ICML 2022
Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data
ICML 2022
Regret Bounds for Stochastic Shortest Path Problems with Linear Function Approximation
ICML 2022
Provably Adversarially Robust Nearest Prototype Classifiers
ICML 2022
First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach
ICML 2022
Accelerating Shapley Explanation via Contributive Cooperator Selection
ICML 2022
Improving Screening Processes via Calibrated Subset Selection
ICML 2022
The Geometry of Robust Value Functions
ICML 2022
Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation
ICML 2022
Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
ICML 2022
Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points
ICML 2022
Understanding Instance-Level Impact of Fairness Constraints
ICML 2022
Finite-Sum Coupled Compositional Stochastic Optimization: Theory and Applications
ICML 2022
How Powerful are Spectral Graph Neural Networks
ICML 2022
More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize
ICML 2022
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm
ICML 2022
Predicting Out-of-Distribution Error with the Projection Norm
ICML 2022
Stabilizing Q-learning with Linear Architectures for Provable Efficient Learning
ICML 2022
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