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Generalization Bounds

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TitleStatusHype
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects—0
Generalization Bounds and Stopping Rules for Learning with Self-Selected Data—0
Generalization Bounds for Adversarial Contrastive Learning—0
Confusion-Based Online Learning and a Passive-Aggressive Scheme—0
Generalization Bounds for Convolutional Neural Networks—0
Generalization Bounds for Data-Driven Numerical Linear Algebra—0
Generalization bounds for deep learning—0
Compressive Sensing and Neural Networks from a Statistical Learning Perspective—0
Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy—0
Generalization Bounds for Dependent Data using Online-to-Batch Conversion—0
A Uniform Generalization Error Bound for Generative Adversarial Networks—0
Generalization Bounds for Equivariant Networks on Markov Data—0
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior—0
Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data—0
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic—0
Co-regularization Based Semi-supervised Domain Adaptation—0
A Mechanism of Implicit Regularization in Deep Learning—0
Generalization Bounds for Label Noise Stochastic Gradient Descent—0
Generalization bounds for learning under graph-dependence: A survey—0
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting—0
Generalization Bounds for Magnitude-Based Pruning via Sparse Matrix Sketching—0
Generalization Bounds for Message Passing Networks on Mixture of Graphons—0
Data-dependent Generalization Bounds for Multi-class Classification—0
Generalization bounds for mixing processes via delayed online-to-PAC conversions—0
Generalization Bounds for Neural Belief Propagation Decoders—0
Generalization Bounds for Neural Networks via Approximate Description Length—0
Generalization bounds for nonparametric regression with β-mixing samples—0
Generalization bounds for regression and classification on adaptive covering input domains—0
Generalization Bounds for Representative Domain Adaptation—0
Generalization Bounds for Set-to-Set Matching with Negative Sampling—0
Generalization Bounds for Stochastic Gradient Descent via Localized -Covers—0
Generalization Bounds for Few-Shot Transfer Learning with Pretrained Classifiers—0
Generalization Bounds for Uniformly Stable Algorithms—0
Generalization Bounds For Unsupervised and Semi-Supervised Learning With Autoencoders—0
Generalization Bounds for Vicinal Risk Minimization Principle—0
Generalization Bounds for (Wasserstein) Robust Optimization—0
Generalization Bounds for Weighted Automata—0
Generalization Bounds in Hybrid Quantum-Classical Machine Learning Models—0
A Functional Perspective on Learning Symmetric Functions with Neural Networks—0
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints—0
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks—0
Generalization Bounds of Surrogate Policies for Combinatorial Optimization Problems—0
Generalization Bounds on Multi-Kernel Learning with Mixed Datasets—0
Generalization Bounds: Perspectives from Information Theory and PAC-Bayes—0
Deep Distributed Optimization for Large-Scale Quadratic Programming—0
Generalization Bounds via Convex Analysis—0
Distribution-dependent concentration inequalities for tighter generalization bounds—0
Generalization Bounds via Information Density and Conditional Information Density—0
Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage—0
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks—0
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