empirical risk minimization

Soft-Label Integration for Robust Toxicity Classification NeurIPS 2024 The Impact of Differential Privacy on Group Disparity Mitigation NAACL 2024 The Nyström method for convex loss functions JMLR 2024 The Price of Implicit Bias in Adversarially Robust Generalization NeurIPS 2024 Towards a statistical theory of data selection under weak supervision ICLR 2024 Toward Student-oriented Teacher Network Training for Knowledge Distillation ICLR 2024 Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy ICLR 2024 Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization NeurIPS 2024 Understanding Domain Generalization: A Noise Robustness Perspective ICLR 2024 Universal Rates of Empirical Risk Minimization NeurIPS 2024 A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition ACL 2023 AGRO: Adversarial discovery of error-prone Groups for Robust Optimization ICLR 2023 An Adaptive Policy to Employ Sharpness-Aware Minimization ICLR 2023 An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization AISTATS 2023 A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm NeurIPS 2023 A Statistical Perspective on Retrieval-Based Models ICML 2023 Avoiding spurious correlations via logit correction ICLR 2023 Data Pruning via Moving-one-Sample-out NeurIPS 2023 Debiased Automatic Speech Recognition for Dysarthric Speech via Sample Reweighting with Sample Affinity Test Interspeech 2023 Deep Perturbation Learning: Enhancing the Network Performance via Image Perturbations ICML 2023 Distributed Algorithms for U-statistics-based Empirical Risk Minimization JMLR 2023 Distributed Personalized Empirical Risk Minimization NeurIPS 2023 Domain Generalization via Heckman-type Selection Models ICLR 2023 Easy Learning from Label Proportions NeurIPS 2023 Empirical Bayes via ERM and Rademacher complexities: the Poisson model COLT 2023