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Theory

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Papers

Minimax Classification under Concept Drift with Multidimensional Adaptation and Performance Guarantees ICML 2022
Towards Understanding Sharpness-Aware Minimization ICML 2022
Understanding Gradient Descent on the Edge of Stability in Deep Learning ICML 2022
H-Consistency Bounds for Surrogate Loss Minimizers ICML 2022
Representation Topology Divergence: A Method for Comparing Neural Network Representations. ICML 2022
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective ICML 2022
Convergence of Invariant Graph Networks ICML 2022
Learning Bellman Complete Representations for Offline Policy Evaluation ICML 2022
Strategies for Safe Multi-Armed Bandits with Logarithmic Regret and Risk ICML 2022
On the Sample Complexity of Learning Infinite-horizon Discounted Linear Kernel MDPs ICML 2022
On Collective Robustness of Bagging Against Data Poisoning ICML 2022
Weisfeiler-Lehman Meets Gromov-Wasserstein ICML 2022
TPC: Transformation-Specific Smoothing for Point Cloud Models ICML 2022
Unified Scaling Laws for Routed Language Models ICML 2022
Online and Consistent Correlation Clustering ICML 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses ICML 2022
Deep symbolic regression for recurrence prediction ICML 2022
Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information ICML 2022
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks ICML 2022
A Neural Tangent Kernel Perspective of GANs ICML 2022
(Non-)Convergence Results for Predictive Coding Networks ICML 2022
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error ICML 2022
The Complexity of k-Means Clustering when Little is Known ICML 2022
Mirror Learning: A Unifying Framework of Policy Optimisation ICML 2022
Adapting k-means Algorithms for Outliers ICML 2022