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Learning Theory

5,334 papers

Papers per year

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123
466
307
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Papers

Accelerating ERM for data-driven algorithm design using output-sensitive techniques NIPS 2024
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers NIPS 2024
Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer NIPS 2024
Universal Rates for Active Learning NIPS 2024
The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions NIPS 2024
Fast Rates for Bandit PAC Multiclass Classification NIPS 2024
Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability NIPS 2024
Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs NIPS 2024
Testing Semantic Importance via Betting NIPS 2024
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields NIPS 2024
Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation NIPS 2024
Deep linear networks for regression are implicitly regularized towards flat minima NIPS 2024
Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context NIPS 2024
Contracting with a Learning Agent NIPS 2024
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit NIPS 2024
An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning NIPS 2024
kGym: A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution NIPS 2024
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously NIPS 2024
Understanding Transformer Reasoning Capabilities via Graph Algorithms NIPS 2024
Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks NIPS 2024
Achieving $\tilde{O}(1/\epsilon)$ Sample Complexity for Constrained Markov Decision Process NIPS 2024
Replicability in Learning: Geometric Partitions and KKM-Sperner Lemma NIPS 2024
Learnability of high-dimensional targets by two-parameter models and gradient flow NIPS 2024
Compact Proofs of Model Performance via Mechanistic Interpretability NIPS 2024
Learning from Snapshots of Discrete and Continuous Data Streams NIPS 2024