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Learning Theory

5,334 papers

Papers per year

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466
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Papers

Truncated Variance Reduced Value Iteration NIPS 2024
MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs NIPS 2024
Most Influential Subset Selection: Challenges, Promises, and Beyond NIPS 2024
On the Expressivity and Sample Complexity of Node-Individualized Graph Neural Networks NIPS 2024
Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning NIPS 2024
Provably Efficient Interactive-Grounded Learning with Personalized Reward NIPS 2024
Targeted Sequential Indirect Experiment Design NIPS 2024
Prospective Learning: Learning for a Dynamic Future NIPS 2024
Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond NIPS 2024
Rethinking the Capacity of Graph Neural Networks for Branching Strategy NIPS 2024
The Power of Extrapolation in Federated Learning NIPS 2024
FairWire: Fair Graph Generation NIPS 2024
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits NIPS 2024
Transductive Active Learning: Theory and Applications NIPS 2024
Almost Surely Asymptotically Constant Graph Neural Networks NIPS 2024
Quantifying the Gain in Weak-to-Strong Generalization NIPS 2024
Towards Principled Graph Transformers NIPS 2024
MEQA: A Benchmark for Multi-hop Event-centric Question Answering with Explanations NIPS 2024
Understanding the Role of Equivariance in Self-supervised Learning NIPS 2024
RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions NIPS 2024
Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation NIPS 2024
Transductive Learning is Compact NIPS 2024
Achieving Constant Regret in Linear Markov Decision Processes NIPS 2024
Average gradient outer product as a mechanism for deep neural collapse NIPS 2024
Using Noise to Infer Aspects of Simplicity Without Learning NIPS 2024