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

A Statistical Perspective on Retrieval-Based Models ICML 2023
An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization AISTATS 2023
A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition ACL 2023
Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation AISTATS 2023
Learning From Biased Soft Labels NIPS 2023
When do Minimax-fair Learning and Empirical Risk Minimization Coincide? ICML 2023
Set-valued Classification with Out-of-distribution Detection for Many Classes JMLR 2023
Federated Learning for Data Streams AISTATS 2023
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm NIPS 2023
Robust Empirical Risk Minimization with Tolerance ALT 2023
Improved Training of Deep Text Clustering EMNLP 2023
Loss-Curvature Matching for Dataset Selection and Condensation AISTATS 2023
End-to-End Learning for Stochastic Optimization: A Bayesian Perspective ICML 2023
Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup ICML 2023
Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete NIPS 2023
Deep Perturbation Learning: Enhancing the Network Performance via Image Perturbations ICML 2023
Understanding and Improving Feature Learning for Out-of-Distribution Generalization NIPS 2023
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation NIPS 2023
Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$-Norm Linear Regression NIPS 2023
The Price of Differential Privacy under Continual Observation ICML 2023
Statistical Learning under Heterogeneous Distribution Shift ICML 2023
Towards Last-layer Retraining for Group Robustness with Fewer Annotations NIPS 2023
Easy Learning from Label Proportions NIPS 2023
On kernel-based statistical learning theory in the mean field limit NIPS 2023
On the Variance, Admissibility, and Stability of Empirical Risk Minimization NIPS 2023