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Generalization Bounds

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TitleStatusHype
Quantum Boosting using Domain-Partitioning HypothesesCode0
Maximum Weighted Loss DiscrepancyCode0
Adapting Neural Architectures Between DomainsCode0
Tighter Information-Theoretic Generalization Bounds from SupersamplesCode0
Consistent Structured Prediction with Max-Min Margin Markov NetworksCode0
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical PerspectiveCode0
Achieving Distributive Justice in Federated Learning via Uncertainty QuantificationCode0
On the Limitations of Fractal Dimension as a Measure of GeneralizationCode0
Relative Flatness and GeneralizationCode0
Implicit Bias of Gradient Descent for Wide Two-layer Neural Networks Trained with the Logistic LossCode0
Implicit Graph Neural Diffusion Networks: Convergence, Generalization, and Over-SmoothingCode0
Importance Weight Estimation and Generalization in Domain Adaptation under Label ShiftCode0
Consistent Sparse Deep Learning: Theory and ComputationCode0
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed LearningCode0
Minimum Description Length and Generalization Guarantees for Representation LearningCode0
An Algorithmic Framework for Fairness ElicitationCode0
Selective Classification via One-Sided PredictionCode0
RATT: Leveraging Unlabeled Data to Guarantee GeneralizationCode0
Model-Powered Conditional Independence TestCode0
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling LawsCode0
Generalization Bounds for Sparse Random Feature ExpansionsCode0
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer MarginCode0
More Flexible PAC-Bayesian Meta-Learning by Learning Learning AlgorithmsCode0
Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-BoundCode0
Operator Learning for Schrödinger Equation: Unitarity, Error Bounds, and Time GeneralizationCode0
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