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Generalization Bounds

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Showing 651–686 of 686 papers

TitleStatusHype
Generalization Bounds via Conditional f-InformationCode0
A PAC-Bayes Analysis of Adversarial RobustnessCode0
Shedding a PAC-Bayesian Light on Adaptive Sliced-Wasserstein DistancesCode0
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization BoundsCode0
Generalization Bounds with Data-dependent Fractal DimensionsCode0
Simple Stochastic and Online Gradient DescentAlgorithms for Pairwise LearningCode0
Towards a Learning Theory of Cause-Effect InferenceCode0
On generalization bounds for deep networks based on loss surface implicit regularizationCode0
Double-Weighting for Covariate Shift AdaptationCode0
Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random FeaturesCode0
Simplified and Unified Analysis of Various Learning Problems by Reduction to Multiple-Instance LearningCode0
Robustness, Privacy, and Generalization of Adversarial TrainingCode0
Robustness to Augmentations as a Generalization metricCode0
Does the Data Induce Capacity Control in Deep Learning?Code0
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization BoundCode0
Learning the optimal Tikhonov regularizer for inverse problemsCode0
An adaptive nearest neighbor rule for classificationCode0
From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task LearningCode0
Learning Where to Learn: Training Distribution Selection for Provable OOD PerformanceCode0
Slicing Mutual Information Generalization Bounds for Neural NetworksCode0
Generalization Performance of Hypergraph Neural NetworksCode0
Understanding the Generalization Benefit of Model Invariance from a Data PerspectiveCode0
Learning Non-Vacuous Generalization Bounds from OptimizationCode0
Generalization Through The Lens Of Leave-One-Out ErrorCode0
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity MeasuresCode0
Sample Compression Unleashed: New Generalization Bounds for Real Valued LossesCode0
Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant LossesCode0
Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain AdaptationCode0
GraphMix: Improved Training of GNNs for Semi-Supervised LearningCode0
A Surprising Linear Relationship Predicts Test Performance in Deep NetworksCode0
Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional RepresentationsCode0
Linear predictor on linearly-generated data with missing values: non consistency and solutionsCode0
Sorting out Lipschitz function approximationCode0
Hausdorff Dimension, Heavy Tails, and Generalization in Neural NetworksCode0
Stable Sample Compression Schemes: New Applications and an Optimal SVM Margin BoundCode0
Heavy Tails in SGD and Compressibility of Overparametrized Neural NetworksCode0
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