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Learning Theory

5,312 papers

Papers per year

Papers

Computational Analyses of the Electoral College: Campaigning Is Hard But Approximately Manageable AAAI 2021
Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games AAAI 2021
The Smoothed Complexity of Computing Kemeny and Slater Rankings AAAI 2021
If You Like Shapley Then You’ll Love the Core AAAI 2021
Incentive-Aware PAC Learning AAAI 2021
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration AAAI 2021
Characterizing the Loss Landscape in Non-Negative Matrix Factorization AAAI 2021
High-Confidence Off-Policy (or Counterfactual) Variance Estimation AAAI 2021
Fitting the Search Space of Weight-sharing NAS with Graph Convolutional Networks AAAI 2021
HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks AAAI 2021
A One-Size-Fits-All Solution to Conservative Bandit Problems AAAI 2021
Regret Bounds for Batched Bandits AAAI 2021
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective AAAI 2021
Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs AAAI 2021
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits AAAI 2021
Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks AAAI 2021
Stochastic Graphical Bandits with Adversarial Corruptions AAAI 2021
On the Adequacy of Untuned Warmup for Adaptive Optimization AAAI 2021
Exact Reduction of Huge Action Spaces in General Reinforcement Learning AAAI 2021
Lenient Regret for Multi-Armed Bandits AAAI 2021
Learning of Structurally Unambiguous Probabilistic Grammars AAAI 2021
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality AAAI 2021
Stability and Generalization of Decentralized Stochastic Gradient Descent AAAI 2021
PAC Learning of Causal Trees with Latent Variables AAAI 2021
Learning Dynamics Models with Stable Invariant Sets AAAI 2021