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Learning Theory

5,334 papers

Papers per year

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Papers

In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization NIPS 2024
Globally Convergent Variational Inference NIPS 2024
Auditing Local Explanations is Hard NIPS 2024
Learning and Transferring Sparse Contextual Bigrams with Linear Transformers NIPS 2024
No-Regret Bandit Exploration based on Soft Tree Ensemble Model NIPS 2024
Implicit Optimization Bias of Next-token Prediction in Linear Models NIPS 2024
Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning NIPS 2024
Distribution Learning with Valid Outputs Beyond the Worst-Case NIPS 2024
A two-scale Complexity Measure for Deep Learning Models NIPS 2024
Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information NIPS 2024
Identifying Equivalent Training Dynamics NIPS 2024
If You Want to Be Robust, Be Wary of Initialization NIPS 2024
Is Score Matching Suitable for Estimating Point Processes? NIPS 2024
Is Knowledge Power? On the (Im)possibility of Learning from Strategic Interactions NIPS 2024
Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion NIPS 2024
Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification NIPS 2024
PAC-Bayes-Chernoff bounds for unbounded losses NIPS 2024
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression NIPS 2024
Sample Complexity of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-Cut NIPS 2024
Least Squares Regression Can Exhibit Under-Parameterized Double Descent NIPS 2024
Understanding the Expressive Power and Mechanisms of Transformer for Sequence Modeling NIPS 2024
Generalization of Hamiltonian algorithms NIPS 2024
Achieving Tractable Minimax Optimal Regret in Average Reward MDPs NIPS 2024
How Far Can Transformers Reason? The Globality Barrier and Inductive Scratchpad NIPS 2024
Chain of Thoughtlessness? An Analysis of CoT in Planning NIPS 2024