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Learning Theory

5,334 papers

Papers per year

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123
466
307
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Papers

The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms NIPS 2024
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games NIPS 2024
On the Saturation Effects of Spectral Algorithms in Large Dimensions NIPS 2024
Stability and Generalization of Asynchronous SGD: Sharper Bounds Beyond Lipschitz and Smoothness NIPS 2024
An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints NIPS 2024
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models NIPS 2024
Overcoming Brittleness in Pareto-Optimal Learning Augmented Algorithms NIPS 2024
Fully Unconstrained Online Learning NIPS 2024
Are Multiple Instance Learning Algorithms Learnable for Instances? NIPS 2024
What do Graph Neural Networks learn? Insights from Tropical Geometry NIPS 2024
Understanding the Expressivity and Trainability of Fourier Neural Operator: A Mean-Field Perspective NIPS 2024
The Power of Resets in Online Reinforcement Learning NIPS 2024
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming NIPS 2024
Pretraining with Random Noise for Fast and Robust Learning without Weight Transport NIPS 2024
SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning NIPS 2024
Sequential Probability Assignment with Contexts: Minimax Regret, Contextual Shtarkov Sums, and Contextual Normalized Maximum Likelihood NIPS 2024
Optimal Parallelization of Boosting NIPS 2024
The Implicit Bias of Heterogeneity towards Invariance: A Study of Multi-Environment Matrix Sensing NIPS 2024
Observational Scaling Laws and the Predictability of Langauge Model Performance NIPS 2024
How to Boost Any Loss Function NIPS 2024
Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation NIPS 2024
4+3 Phases of Compute-Optimal Neural Scaling Laws NIPS 2024
Preference-based Pure Exploration NIPS 2024
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss NIPS 2024
Cardinality-Aware Set Prediction and Top-$k$ Classification NIPS 2024