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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
Online Dense Subgraph Discovery via Blurred-Graph Feedback
ICML 2020
Learning with Good Feature Representations in Bandits and in RL with a Generative Model
ICML 2020
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
ICML 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors
ICML 2020
A Mean Field Analysis Of Deep ResNet And Beyond: Towards Provably Optimization Via Overparameterization From Depth
ICML 2020
Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle
ICML 2020
On Approximate Thompson Sampling with Langevin Algorithms
ICML 2020
On the Global Convergence Rates of Softmax Policy Gradient Methods
ICML 2020
The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture
ICML 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise
ICML 2020
Consistent Estimators for Learning to Defer to an Expert
ICML 2020
Unique Properties of Flat Minima in Deep Networks
ICML 2020
In Defense of Uniform Convergence: Generalization via Derandomization with an Application to Interpolating Predictors
ICML 2020
Consistent Structured Prediction with Max-Min Margin Markov Networks
ICML 2020
Recovery of Sparse Signals from a Mixture of Linear Samples
ICML 2020
Performative Prediction
ICML 2020
Budgeted Online Influence Maximization
ICML 2020
The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons
ICML 2020
Near-optimal Regret Bounds for Stochastic Shortest Path
ICML 2020
Improved Sleeping Bandits with Stochastic Action Sets and Adversarial Rewards
ICML 2020
From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model
ICML 2020
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
ICML 2020
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
ICML 2020
A Sample Complexity Separation between Non-Convex and Convex Meta-Learning
ICML 2020
Optimistic Policy Optimization with Bandit Feedback
ICML 2020
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