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Generalization Bounds

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TitleStatusHype
A PAC-Bayesian Generalization Bound for Equivariant Networks—0
A PAC-Bayesian Tutorial with A Dropout Bound—0
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions—0
Apportioned Margin Approach for Cost Sensitive Large Margin Classifiers—0
Approximate Description Length, Covering Numbers, and VC Dimension—0
A Primal-Dual link between GANs and Autoencoders—0
A Rademacher Complexity Based Method fo rControlling Power and Confidence Level in Adaptive Statistical Analysis—0
Architecture independent generalization bounds for overparametrized deep ReLU networks—0
A study of the classification of low-dimensional data with supervised manifold learning—0
A Limitation of the PAC-Bayes Framework—0
Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage—0
A Theory of Label Propagation for Subpopulation Shift—0
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes—0
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise—0
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks—0
Aggregation Weighting of Federated Learning via Generalization Bound Estimation—0
A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning—0
Data-dependent Generalization Bounds via Variable-Size Compressibility—0
Data-Dependent Stability of Stochastic Gradient Descent—0
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming—0
Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank—0
Coarse-Refinement Dilemma: On Generalization Bounds for Data Clustering—0
A Novel Plug-and-Play Approach for Adversarially Robust Generalization—0
A Note on High-Probability versus In-Expectation Guarantees of Generalization Bounds in Machine Learning—0
A note on generalization bounds for losses with finite moments—0
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks—0
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting—0
Generalization Bounds for Quantum Learning via Rényi Divergences—0
An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics—0
A Generalization Bound of Deep Neural Networks for Dependent Data—0
Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data—0
Can SGD Learn Recurrent Neural Networks with Provable Generalization?—0
An Exponential Efron-Stein Inequality for Lq Stable Learning Rules—0
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data—0
Chaining Mutual Information and Tightening Generalization Bounds—0
A Nonlinear Kernel Support Matrix Machine for Matrix Learning—0
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics—0
Classification with Deep Neural Networks and Logistic Loss—0
Class-wise Generalization Error: an Information-Theoretic Analysis—0
On the Sample Complexity of Stability Constrained Imitation Learning—0
Boosting with the Logistic Loss is Consistent—0
Cold Posteriors through PAC-Bayes—0
A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction—0
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization—0
Complex-valued embeddings of generic proximity data—0
Compressing Heavy-Tailed Weight Matrices for Non-Vacuous Generalization Bounds—0
Compression Implies Generalization—0
Compute-Optimal LLMs Provably Generalize Better With Scale—0
Adaptive Data Analysis for Growing Data—0
Boosting the kernelized shapelets: Theory and algorithms for local features—0
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