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Learning Theory

5312 directly classified papers

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Papers

Generalization Bounds via Conditional $f$-Information NIPS 2024
Global Convergence in Training Large-Scale Transformers NIPS 2024
On the Stability and Generalization of Meta-Learning NIPS 2024
Learning via Surrogate PAC-Bayes NIPS 2024
A Near-optimal Algorithm for Learning Margin Halfspaces with Massart Noise NIPS 2024
On the uniqueness of solution for the Bellman equation of LTL objectives L4DC 2024
Optimal Design for Human Preference Elicitation NIPS 2024
Towards a theory of how the structure of language is acquired by deep neural networks NIPS 2024
When Is Inductive Inference Possible? NIPS 2024
On the Performance of Empirical Risk Minimization with Smoothed Data COLT 2024
Accelerating Matroid Optimization through Fast Imprecise Oracles NIPS 2024
Is Efficient PAC Learning Possible with an Oracle That Responds "Yes" or "No"? COLT 2024
Derandomizing Multi-Distribution Learning NIPS 2024
The Real Price of Bandit Information in Multiclass Classification COLT 2024
The Price of Implicit Bias in Adversarially Robust Generalization NIPS 2024
GRASP: A Novel Benchmark for Evaluating Language GRounding and Situated Physics Understanding in Multimodal Language Models IJCAI 2024
Wide Two-Layer Networks can Learn from Adversarial Perturbations NIPS 2024
On the Computability of Robust PAC Learning COLT 2024
Learning Cut Generating Functions for Integer Programming NIPS 2024
Inherent limitations of dimensions for characterizing learnability of distribution classes COLT 2024
Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity NIPS 2024
Linear bandits with polylogarithmic minimax regret COLT 2024
Consistency of Neural Causal Partial Identification NIPS 2024
Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks NIPS 2024
Learning to Understand: Identifying Interactions via the Möbius Transform NIPS 2024