conftrace_

empirical risk minimization

352 papers

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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

Improved Algorithms for Agnostic Pool-based Active Classification ICML 2021
SWAD: Domain Generalization by Seeking Flat Minima NIPS 2021
Oracle Efficient Private Non-Convex Optimization ICML 2020
A Group-Theoretic Framework for Data Augmentation JMLR 2020
Hierarchically Robust Representation Learning CVPR 2020
Approximate Cross-Validation for Structured Models NIPS 2020
Smoothly Bounding User Contributions in Differential Privacy NIPS 2020
Probably Approximately Correct Constrained Learning NIPS 2020
Statistically Preconditioned Accelerated Gradient Method for Distributed Optimization ICML 2020
A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval NIPS 2020
On Suboptimality of Least Squares with Application to Estimation of Convex Bodies COLT 2020
Risk Bounds for Reservoir Computing JMLR 2020
Robust high dimensional learning for Lipschitz and convex losses JMLR 2020
Fast Rates for General Unbounded Loss Functions: From ERM to Generalized Bayes JMLR 2020
Empirical Risk Minimization in the Non-interactive Local Model of Differential Privacy JMLR 2020
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent JMLR 2020
Do Subsampled Newton Methods Work for High-Dimensional Data? AAAI 2020
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy AISTATS 2020
A Statistical Learning Approach to Modal Regression JMLR 2020
Approximate Cross-validation: Guarantees for Model Assessment and Selection AISTATS 2020
Sharp Asymptotics and Optimal Performance for Inference in Binary Models AISTATS 2020
Learning Causal Effects via Weighted Empirical Risk Minimization NIPS 2020
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions AISTATS 2020
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach AISTATS 2020
Learning From Multi-Dimensional Partial Labels IJCAI 2020