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generalization bound

652 papers

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Co-occurring keywords

learning theory (519) neural network (6616) stochastic gradient descent (1091) algorithmic stability (82) rademacher complexity (109) sample complexity (1169) generalization error (285) pac-bayes bound (53) kernel methods (1097) neural network optimization (1293)

Papers

Generalization Bounds for Label Noise Stochastic Gradient Descent AISTATS 2024
Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance JMLR 2024
Fairness without Harm: An Influence-Guided Active Sampling Approach NIPS 2024
Stable Minima Cannot Overfit in Univariate ReLU Networks: Generalization by Large Step Sizes NIPS 2024
Convolutional Spectral Kernel Learning with Generalization Guarantees (Abstract Reprint) AAAI 2024
Functions with average smoothness: structure, algorithms, and learning JMLR 2024
PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees CVPR 2024
Length independent PAC-Bayes bounds for Simple RNNs AISTATS 2024
Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data JMLR 2024
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks JMLR 2024
Mentored Learning: Improving Generalization and Convergence of Student Learner JMLR 2024
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity JMLR 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024
On the Generalization Ability of Unsupervised Pretraining AISTATS 2024
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization NIPS 2024
Test-Time Dynamic Image Fusion NIPS 2024
Generalization and Stability of Interpolating Neural Networks with Minimal Width JMLR 2024
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024
Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees AISTATS 2024
To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models AISTATS 2024
Generalization Bounds via Conditional $f$-Information NIPS 2024
Stability and L2-penalty in Model Averaging JMLR 2024
Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure AAAI 2024
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning NIPS 2024
Towards Understanding Generalization of Macro-AUC in Multi-label Learning ICML 2023