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Generalization Bounds

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TitleStatusHype
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach—0
Explaining generalization in deep learning: progress and fundamental limits—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
Extrapolation and Spectral Bias of Neural Nets with Hadamard Product: a Polynomial Net Study—0
Failures of model-dependent generalization bounds for least-norm interpolation—0
Fairness-aware Federated Learning—0
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective—0
Fair Off-Policy Learning from Observational Data—0
Fantastic Generalization Measures are Nowhere to be Found—0
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data—0
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes—0
f-Domain-Adversarial Learning: Theory and Algorithms for Unsupervised Domain Adaptation with Neural Networks—0
Advocating for the Silent: Enhancing Federated Generalization for Non-Participating Clients—0
Federated Variational Inference: Towards Improved Personalization and Generalization—0
Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent—0
Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random—0
Fine-grained Generalization Analysis of Vector-valued Learning—0
Fine-grained Generalization Analysis of Structured Output Prediction—0
Formal limitations of sample-wise information-theoretic generalization bounds—0
Foundations of Coupled Nonlinear Dimensionality Reduction—0
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms—0
From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD—0
Functions with average smoothness: structure, algorithms, and learning—0
Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Ability—0
Generalization Analysis for Contrastive Representation Learning—0
Generalization Analysis for Contrastive Representation Learning under Non-IID Settings—0
Generalization Analysis for Deep Contrastive Representation Learning—0
Generalization and Representational Limits of Graph Neural Networks—0
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage—0
Generalization Bounds and Consistency for Latent Structural Probit and Ramp Loss—0
Generalization Bounds and Model Complexity for Kolmogorov-Arnold Networks—0
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
Generalization Bounds for Convolutional Neural Networks—0
Generalization Bounds for Data-Driven Numerical Linear Algebra—0
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