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Generalization Bounds

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Showing 601–650 of 686 papers

TitleStatusHype
Coarse-Refinement Dilemma: On Generalization Bounds for Data Clustering—0
Cold Posteriors through PAC-Bayes—0
Generalization Bounds with Minimal Dependency on Hypothesis Class via Distributionally Robust Optimization—0
Complex-valued embeddings of generic proximity data—0
Compressing Heavy-Tailed Weight Matrices for Non-Vacuous Generalization Bounds—0
Compression Implies Generalization—0
Compute-Optimal LLMs Provably Generalize Better With Scale—0
Conditioning and Processing: Techniques to Improve Information-Theoretic Generalization Bounds—0
Confusion-Based Online Learning and a Passive-Aggressive Scheme—0
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality—0
Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions—0
Convex Surrogate Loss Functions for Contextual Pricing with Transaction Data—0
Co-regularization Based Semi-supervised Domain Adaptation—0
Data Augmentation vs. Equivariant Networks: A Theory of Generalization on Dynamics Forecasting—0
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds—0
Data-dependent Generalization Bounds for Multi-class Classification—0
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise—0
Data-dependent Generalization Bounds via Variable-Size Compressibility—0
Data-dependent PAC-Bayes priors via differential privacy—0
Data-Dependent Stability Analysis of Adversarial Training—0
Data-Dependent Stability of Stochastic Gradient Descent—0
Data-Driven Neural Certificate Synthesis—0
Generalization Bound and Learning Methods for Data-Driven Projections in Linear Programming—0
On Generalization of Decentralized Learning with Separable Data—0
Decoupling Gating from Linearity—0
Deep Distributed Optimization for Large-Scale Quadratic Programming—0
Deep multi-Wasserstein unsupervised domain adaptation—0
Deep Networks as Logical Circuits: Generalization and Interpretation—0
De-randomized PAC-Bayes Margin Bounds: Applications to Non-convex and Non-smooth Predictors—0
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience—0
Diffusion Random Feature Model—0
Dimensionality-Dependent Generalization Bounds for k-Dimensional Coding Schemes—0
Dimension Free Generalization Bounds for Non Linear Metric Learning—0
Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization—0
Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks—0
Distribution-dependent concentration inequalities for tighter generalization bounds—0
Domain Adaptation: Learning Bounds and Algorithms—0
Dropout Training, Data-dependent Regularization, and Generalization Bounds—0
Dynamical simulation via quantum machine learning with provable generalization—0
Effective Distributed Learning with Random Features: Improved Bounds and Algorithms—0
Efficient and Reliable Overlay Networks for Decentralized Federated Learning—0
Efron-Stein PAC-Bayesian Inequalities—0
Empirical Risk Landscape Analysis for Understanding Deep Neural Networks—0
Encoding-dependent generalization bounds for parametrized quantum circuits—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
Estimating Lipschitz constants of monotone deep equilibrium models—0
Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness—0
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