conftrace_

empirical risk minimization

352 papers

Explore in graph

Also known as

ERM

Co-occurring keywords

convex optimization (1321) stochastic optimization (1060) differential privacy (1016) stochastic gradient descent (1091) learning theory (519) generalization bound (652) sample complexity (1169) non-convex optimization (547) domain generalization (1522) distributionally robust optimization (185)

Papers

Probably Approximately Correct Constrained Learning NIPS 2020
A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval NIPS 2020
Self-Adaptive Training: beyond Empirical Risk Minimization NIPS 2020
A Group-Theoretic Framework for Data Augmentation NIPS 2020
Learning Causal Effects via Weighted Empirical Risk Minimization NIPS 2020
Do Subsampled Newton Methods Work for High-Dimensional Data? AAAI 2020
Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization AISTATS 2020
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach AISTATS 2020
Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates ICML 2020
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction JMLR 2020
Leverage Score Sampling for Faster Accelerated Regression and ERM ALT 2020
On Suboptimality of Least Squares with Application to Estimation of Convex Bodies COLT 2020
Online Learning from Data Streams with Varying Feature Spaces AAAI 2019
Theoretical Analysis of Label Distribution Learning AAAI 2019
Better generalization with less data using robust gradient descent ICML 2019
Nonconvex Variance Reduced Optimization with Arbitrary Sampling ICML 2019
Classification from Positive, Unlabeled and Biased Negative Data ICML 2019
Latent Semantics Encoding for Label Distribution Learning IJCAI 2019
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy ICML 2019
On Medians of (Randomized) Pairwise Means ICML 2019
Acceleration of SVRG and Katyusha X by Inexact Preconditioning ICML 2019
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization ICML 2019
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019
A tight excess risk bound via a unified PAC-Bayesian–Rademacher–Shtarkov–MDL complexity ALT 2019
Stagewise Training Accelerates Convergence of Testing Error Over SGD NIPS 2019