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Generalization Bounds

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Showing 501–550 of 686 papers

TitleStatusHype
Regularized Gradient Boosting—0
A Primal-Dual link between GANs and Autoencoders—0
Simplified and Unified Analysis of Various Learning Problems by Reduction to Multiple-Instance LearningCode0
Coarse-Refinement Dilemma: On Generalization Bounds for Data Clustering—0
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent EstimatesCode0
Learning-Based Low-Rank Approximations—0
On Generalization Bounds of a Family of Recurrent Neural Networks—0
Diametrical Risk Minimization: Theory and ComputationsCode0
Global Capacity Measures for Deep ReLU Networks via Path Sampling—0
Sharper bounds for uniformly stable algorithms—0
Improved Generalization Bounds of Group Invariant / Equivariant Deep Networks via Quotient Feature Spaces—0
Generalization Bounds for Neural Networks via Approximate Description Length—0
Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer MarginCode0
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks—0
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics—0
A Rademacher Complexity Based Method fo rControlling Power and Confidence Level in Adaptive Statistical Analysis—0
Generalization Bounds for Convolutional Neural Networks—0
Partial differential equation regularization for supervised machine learning—0
Margin-Based Generalization Lower Bounds for Boosted Classifiers—0
Wide Neural Networks are Interpolating Kernel Methods: Impact of Initialization on Generalization—0
A Mechanism of Implicit Regularization in Deep Learning—0
Knowledge Graph Embedding: A Probabilistic Perspective and Generalization Bounds—0
A Uniform Generalization Error Bound for Generative Adversarial Networks—0
PAC-Bayesian Neural Network Bounds—0
GraphMix: Improved Training of GNNs for Semi-Supervised LearningCode0
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation—0
Efron-Stein PAC-Bayesian Inequalities—0
On the Downstream Performance of Compressed Word EmbeddingsCode0
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes—0
How much data is sufficient to learn high-performing algorithms? Generalization guarantees for data-driven algorithm design—0
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant LossesCode0
Learning from weakly dependent data under Dobrushin's condition—0
Robust Regression for Safe Exploration in Control—0
Decoupling Gating from Linearity—0
Stable Rank Normalization for Improved Generalization in Neural Networks and GANs—0
Maximum Weighted Loss DiscrepancyCode0
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience—0
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks—0
Generalization bounds for deep convolutional neural networks—0
An adaptive nearest neighbor rule for classificationCode0
Generalization Bounds in the Predict-then-Optimize Framework—0
An Algorithmic Framework for Fairness ElicitationCode0
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural NetworksCode0
Gradient Descent can Learn Less Over-parameterized Two-layer Neural Networks on Classification Problems—0
The role of invariance in spectral complexity-based generalization bounds—0
Stability and Generalization of Graph Convolutional Neural Networks—0
On Tighter Generalization Bounds for Deep Neural Networks: CNNs, ResNets, and Beyond—0
ON BREIMAN’S DILEMMA IN NEURAL NETWORKS: SUCCESS AND FAILURE OF NORMALIZED MARGINS—0
Deep multi-Wasserstein unsupervised domain adaptation—0
Stability and Optimization Error of Stochastic Gradient Descent for Pairwise Learning—0
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