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Generalization Bounds

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TitleStatusHype
Generalization Bounds for Causal Regression: Insights, Guarantees and Sensitivity AnalysisCode0
Generalization Bounds for Learning with Linear, Polygonal, Quadratic and Conic Side KnowledgeCode0
Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical PerspectiveCode0
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization BoundsCode0
Learning the optimal Tikhonov regularizer for inverse problemsCode0
Generalization Performance of Hypergraph Neural NetworksCode0
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity MeasuresCode0
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization BoundsCode0
Minimum Description Length and Generalization Guarantees for Representation LearningCode0
Stability and Generalization of Stochastic Gradient Methods for Minimax ProblemsCode0
Estimating the Success of Unsupervised Image to Image TranslationCode0
Deep Networks as Logical Circuits: Generalization and Interpretation—0
A Theory of Label Propagation for Subpopulation Shift—0
Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage—0
(Almost) No Label No Cry—0
Deep Distributed Optimization for Large-Scale Quadratic Programming—0
Decoupling Gating from Linearity—0
On Generalization of Decentralized Learning with Separable Data—0
A study of the classification of low-dimensional data with supervised manifold learning—0
A Limitation of the PAC-Bayes Framework—0
Adversarial Networks and Autoencoders: The Primal-Dual Relationship and Generalization Bounds—0
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming—0
Data-Driven Neural Certificate Synthesis—0
Architecture independent generalization bounds for overparametrized deep ReLU networks—0
Data-Dependent Stability of Stochastic Gradient Descent—0
Data-Dependent Stability Analysis of Adversarial Training—0
A Rademacher Complexity Based Method fo rControlling Power and Confidence Level in Adaptive Statistical Analysis—0
Algorithms for Learning Kernels Based on Centered Alignment—0
Data-dependent PAC-Bayes priors via differential privacy—0
Data-dependent Generalization Bounds via Variable-Size Compressibility—0
A Primal-Dual link between GANs and Autoencoders—0
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise—0
Data-dependent Generalization Bounds for Multi-class Classification—0
Approximate Description Length, Covering Numbers, and VC Dimension—0
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise—0
Adversarial Multiple Source Domain Adaptation—0
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks—0
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds—0
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting—0
Apportioned Margin Approach for Cost Sensitive Large Margin Classifiers—0
Co-regularization Based Semi-supervised Domain Adaptation—0
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions—0
Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data—0
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions—0
A PAC-Bayesian Tutorial with A Dropout Bound—0
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks—0
Adaptive Metric Dimensionality Reduction—0
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality—0
Confusion-Based Online Learning and a Passive-Aggressive Scheme—0
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss—0
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