conftrace_

generalization bound

652 papers

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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

Fine-Grained Theoretical Analysis of Federated Zeroth-Order Optimization NIPS 2023
A Unified Recipe for Deriving (Time-Uniform) PAC-Bayes Bounds JMLR 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion AISTATS 2023
On the Implicit Bias of Linear Equivariant Steerable Networks NIPS 2023
Convolutional Persistence as a Remedy to Neural Model Analysis AISTATS 2023
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks ICML 2023
Certified Robust Neural Networks: Generalization and Corruption Resistance ICML 2023
Time-Independent Information-Theoretic Generalization Bounds for SGLD NIPS 2023
Learning via Wasserstein-Based High Probability Generalisation Bounds NIPS 2023
A unified framework for information-theoretic generalization bounds NIPS 2023
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks AAAI 2023
Generalization Bounds for Inductive Matrix Completion in Low-Noise Settings AAAI 2023
Theory and Algorithm for Batch Distribution Drift Problems AISTATS 2023
GradPU: Positive-Unlabeled Learning via Gradient Penalty and Positive Upweighting AAAI 2023
PAC-tuning: Fine-tuning Pre-trained Language Models with PAC-driven Perturbed Gradient Descent EMNLP 2023
Sparsity-aware generalization theory for deep neural networks COLT 2023
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation AISTATS 2023
NICO++: Towards Better Benchmarking for Domain Generalization CVPR 2023
Diverse Cotraining Makes Strong Semi-Supervised Segmentor ICCV 2023
PAC-Bayesian Offline Contextual Bandits With Guarantees ICML 2023
Provable Pathways: Learning Multiple Tasks over Multiple Paths AAAI 2023
Stability-Based Generalization Analysis for Mixtures of Pointwise and Pairwise Learning AAAI 2023
Learning Trajectories are Generalization Indicators NIPS 2023
An Information Theory Perspective on Variance-Invariance-Covariance Regularization NIPS 2023
Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape ICML 2023