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Generalization Bounds

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TitleStatusHype
Encoding-dependent generalization bounds for parametrized quantum circuits—0
Generalization Bounds for Deep Transfer Learning Using Majority Predictor Accuracy—0
Block Contextual MDPs for Continual Learning—0
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors—0
Entropy-SGD optimizes the prior of a PAC-Bayes bound: Data-dependent PAC-Bayes priors via differential privacy—0
Epistemic Errors of Imperfect Multitask Learners When Distributions Shift—0
Equivariant score-based generative models provably learn distributions with symmetries efficiently—0
Boosting the Confidence of Near-Tight Generalization Bounds for Uniformly Stable Randomized Algorithms—0
Generalization Bounds for Equivariant Networks on Markov Data—0
Estimating Lipschitz constants of monotone deep equilibrium models—0
Boosting with the Logistic Loss is Consistent—0
Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness—0
Domain Adaptation: Learning Bounds and Algorithms—0
BARACK: Partially Supervised Group Robustness With Guarantees—0
Explaining generalization in deep learning: progress and fundamental limits—0
Detached Error Feedback for Distributed SGD with Random Sparsification—0
An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics—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
A Uniform Generalization Error Bound for Generative Adversarial Networks—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
Classification with Deep Neural Networks and Logistic Loss—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
A Mechanism of Implicit Regularization in Deep Learning—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
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization—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
Compute-Optimal LLMs Provably Generalize Better With Scale—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
A Functional Perspective on Learning Symmetric Functions with Neural Networks—0
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