conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Theory

4,955 papers

Papers per year

1
4
37
72
447
426
'00
'05
'10
'15
'20
'25

Papers

From Shapley Values to Generalized Additive Models and back AISTATS 2023
Testing of Horn Samplers AISTATS 2023
Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces AISTATS 2023
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning AISTATS 2023
Model-X Sequential Testing for Conditional Independence via Testing by Betting AISTATS 2023
A Statistical Analysis of Polyak-Ruppert Averaged Q-Learning AISTATS 2023
A Finite Sample Complexity Bound for Distributionally Robust Q-learning AISTATS 2023
Convergence of Stein Variational Gradient Descent under a Weaker Smoothness Condition AISTATS 2023
On the bias of K-fold cross validation with stable learners AISTATS 2023
Provably Efficient Reinforcement Learning via Surprise Bound AISTATS 2023
Active Learning for Single Neuron Models with Lipschitz Non-Linearities AISTATS 2023
Oblivious near-optimal sampling for multidimensional signals with Fourier constraints AISTATS 2023
Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics AISTATS 2023
Risk Bounds on Aleatoric Uncertainty Recovery AISTATS 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion AISTATS 2023
Precision Recall Cover: A Method For Assessing Generative Models AISTATS 2023
INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation AISTATS 2023
Recurrent Neural Networks and Universal Approximation of Bayesian Filters AISTATS 2023
On double-descent in uncertainty quantification in overparametrized models AISTATS 2023
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources AISTATS 2023
PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise AISTATS 2023
Optimal robustness-consistency tradeoffs for learning-augmented metrical task systems AISTATS 2023
On The Convergence Of Policy Iteration-Based Reinforcement Learning With Monte Carlo Policy Evaluation AISTATS 2023
Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier AISTATS 2023