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

Group-realizable multi-group learning by minimizing empirical risk ALT 2026
Distribution Shift Is Key to Learning Invariant Prediction AAAI 2026
Bridging Lifelong and Multi-Task Representation Learning: An Algorithm and a Complexity Measure ALT 2026
Complexity of Vector-valued Prediction: From Linear Models to Stochastic Convex Optimization ALT 2026
Learning from Synthetic Data: Limitations of ERM ALT 2026
Let Samples Speak: Mitigating Spurious Correlation by Exploiting the Clusterness of Samples CVPR 2025
Gradient Extrapolation for Debiased Representation Learning ICCV 2025
ERM++: An Improved Baseline for Domain Generalization WACV 2025
Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization AAAI 2025
What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization ICCV 2025
Learn from Failure: Causality-guided Contrastive Learning for Generalizable Implicit Hate Speech Detection COLING 2025
Boosting Test Performance with Importance Sampling--a Subpopulation Perspective AAAI 2025
Towards Improved Risk Bounds for Transductive Learning IJCAI 2025
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition JMLR 2024
Optimistic Rates for Learning from Label Proportions COLT 2024
Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024
The Nyström method for convex loss functions JMLR 2024
Is Efficient PAC Learning Possible with an Oracle That Responds "Yes" or "No"? COLT 2024
On Convex Optimization with Semi-Sensitive Features COLT 2024
Sharp error bounds for imbalanced classification: how many examples in the minority class? AISTATS 2024
Agnostic Multi-Robust Learning using ERM AISTATS 2024
On the Stability and Generalization of Meta-Learning NIPS 2024
Learning with a linear loss function: excess risk and estimation bounds for ERM, minmax MOM and their regularized versions with applications to robustness in sparse PCA. JMLR 2024
Regularization and Optimal Multiclass Learning COLT 2024
Mitigating Spurious Correlations via Disagreement Probability NIPS 2024