conftrace_

generalization error

285 papers

Explore in graph

Also known as

GE

Co-occurring keywords

generalization bound (652) stochastic gradient descent (1091) neural network (6616) learning theory (519) double descent (52) sample complexity (1169) active learning (1301) gradient descent (1144) support vector machine (978) neural network optimization (1293)

Papers

Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent (Abstract Reprint) AAAI 2026
Scaling Law Analysis in Federated Learning: How to Select the Optimal Model Size? AAAI 2026
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes CVPR 2025
(1+1) Genetic Programming with Functionally Complete Instruction Sets Can Evolve Boolean Conjunctions and Disjunctions with Arbitrarily Small Error AAAI 2025
Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions JMLR 2025
On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel Theory JMLR 2025
FedHB: Hierarchical Bayesian Federated Learning JMLR 2025
Training Data Provenance Verification: Did Your Model Use Synthetic Data from My Generative Model for Training? CVPR 2025
A Priori Estimation of the Approximation, Optimization and Generalization Errors of Random Neural Networks for Solving Partial Differential Equations IJCAI 2025
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025
Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime JMLR 2025
Stability and Generalization for Stochastic (Compositional) Optimizations IJCAI 2025
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? AAAI 2025
On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes JMLR 2025
Sample Complexity of Linear Regression Models for Opinion Formation in Networks AAAI 2025
A two-scale Complexity Measure for Deep Learning Models NIPS 2024
Understanding Scaling Laws with Statistical and Approximation Theory for Transformer Neural Networks on Intrinsically Low-dimensional Data NIPS 2024
Critical Gap Between Generalization Error and Empirical Error in Active Learning WACV 2024
Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization NIPS 2024
Test-Time Dynamic Image Fusion NIPS 2024
Better-than-KL PAC-Bayes Bounds COLT 2024
Multivariate Time Series Forecasting By Graph Attention Networks With Theoretical Guarantees AISTATS 2024
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression NIPS 2024
A Comprehensive Analysis on the Learning Curve in Kernel Ridge Regression NIPS 2024
Asymptotic Characterisation of the Performance of Robust Linear Regression in the Presence of Outliers AISTATS 2024