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Generalization Bounds

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TitleStatusHype
Regularized Gradient Boosting—0
Regularized Proportional Fairness Mechanism for Resource Allocation Without Money—0
Reinterpreting causal discovery as the task of predicting unobserved joint statistics—0
Relative Deviation Learning Bounds and Generalization with Unbounded Loss Functions—0
Relative Deviation Margin Bounds—0
Towards Data-Algorithm Dependent Generalization: a Case Study on Overparameterized Linear Regression—0
Representation and Regression Problems in Neural Networks: Relaxation, Generalization, and Numerics—0
Reward Generalization in RLHF: A Topological Perspective—0
Reweighted Mixup for Subpopulation Shift—0
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method—0
Risk Bounds for Low Cost Bipartite Ranking—0
Robust Generalization of Quadratic Neural Networks via Function Identification—0
Robust Model Evaluation over Large-scale Federated Networks—0
Robustness and Generalization for Metric Learning—0
Robustness Implies Generalization via Data-Dependent Generalization Bounds—0
Robust Regression for Safe Exploration in Control—0
Estimating the Success of Unsupervised Image to Image TranslationCode0
Provable Guarantees for Gradient-Based Meta-LearningCode0
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization BoundsCode0
A General Framework for the Practical Disintegration of PAC-Bayesian BoundsCode0
Stability Analysis and Generalization Bounds of Adversarial TrainingCode0
Pseudo-Bayesian Learning with Kernel Fourier Transform as PriorCode0
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List StabilityCode0
Tighter Learning Guarantees on Digital Computers via Concentration of Measure on Finite SpacesCode0
On the Downstream Performance of Compressed Word EmbeddingsCode0
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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