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Generalization Bounds

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TitleStatusHype
Generalization Bounds on Multi-Kernel Learning with Mixed Datasets—0
Generalization Bounds: Perspectives from Information Theory and PAC-Bayes—0
Generalization Bounds via Convex Analysis—0
Generalization bounds via distillation—0
Generalization Bounds via Information Density and Conditional Information Density—0
Generalization Error Bounds for Iterative Recovery Algorithms Unfolded as Neural Networks—0
Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs—0
Generalization Guarantee of SGD for Pairwise Learning—0
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior—0
Generalization Guarantees for Neural Architecture Search with Train-Validation Split—0
Generalization Guarantees via Algorithm-dependent Rademacher Complexity—0
Generalization in Cooperative Multi-Agent Systems—0
Generalization In Multi-Objective Machine Learning—0
Generalization in Supervised Learning Through Riemannian Contraction—0
Generalization of GANs and overparameterized models under Lipschitz continuity—0
Generalization of Graph Neural Networks through the Lens of Homomorphism—0
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks—0
Generalization of Scaled Deep ResNets in the Mean-Field Regime—0
Generalization Bounds using Lower Tail Exponents in Stochastic Optimizers—0
Generalization Through Growth: Hidden Dynamics Controls Depth Dependence—0
Generalizing across Temporal Domains with Koopman Operators—0
Global Capacity Measures for Deep ReLU Networks via Path Sampling—0
Graph-based Generalization Bounds for Learning Binary Relations—0
Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs—0
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings—0
Guaranteed Classification via Regularized Similarity Learning—0
Heating up decision boundaries: isocapacitory saturation, adversarial scenarios and generalization bounds—0
Hedging Complexity in Generalization via a Parametric Distributionally Robust Optimization Framework—0
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives—0
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate—0
High Probability Generalization Bounds for Minimax Problems with Fast Rates—0
How much data is sufficient to learn high-performing algorithms? Generalization guarantees for data-driven algorithm design—0
Generalization Bounds in the Presence of Outliers: a Median-of-Means Study—0
How To Prevent the Poor Performance Clients for Personalized Federated Learning?—0
How Well Can Generative Adversarial Networks Learn Densities: A Nonparametric View—0
Huber Additive Models for Non-stationary Time Series Analysis—0
Human Rademacher Complexity—0
Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability—0
Identifying and Estimating Causal Effects under Weak Overlap by Generative Prognostic Model—0
Improved Generalization Bound for Deep Neural Networks Using Geometric Functional Analysis—0
Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces—0
Improved Generalization Bounds for Communication Efficient Federated Learning—0
Improved Generalization Bounds for Adversarially Robust Learning—0
Improved Generalization Risk Bounds for Meta-Learning with PAC-Bayes-kl Analysis—0
Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning—0
Improved Margin Generalization Bounds for Voting Classifiers—0
Improved Sample Complexities for Deep Neural Networks and Robust Classification via an All-Layer Margin—0
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm—0
Improving Equivariant Networks with Probabilistic Symmetry Breaking—0
Theoretical and Empirical Advances in Forest Pruning—0
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