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Theory

4950 directly classified papers

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Papers

Oblivious near-optimal sampling for multidimensional signals with Fourier constraints 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
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources AISTATS 2023
Ridges, Neural Networks, and the Radon Transform JMLR 2023
Sensing Theorems for Unsupervised Learning in Linear Inverse Problems JMLR 2023
When Locally Linear Embedding Hits Boundary JMLR 2023
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries JMLR 2023
Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels JMLR 2023
Reinforcement Learning for Joint Optimization of Multiple Rewards JMLR 2023
The Implicit Bias of Benign Overfitting JMLR 2023
Deep linear networks can benignly overfit when shallow ones do JMLR 2023
Generalization error bounds for multiclass sparse linear classifiers JMLR 2023
Metrizing Weak Convergence with Maximum Mean Discrepancies JMLR 2023
GANs as Gradient Flows that Converge JMLR 2023
Revisiting minimum description length complexity in overparameterized models JMLR 2023
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds JMLR 2023
Towards Equivariant Optical Flow Estimation With Deep Learning WACV 2023
Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning ICML 2023
Dimension-independent Certified Neural Network Watermarks via Mollifier Smoothing ICML 2023
Inflow, Outflow, and Reciprocity in Machine Learning ICML 2023
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts ICML 2023