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

Open Problem: Can Local Regularization Learn All Multiclass Problems? COLT 2024
Mitigating Spurious Correlations via Disagreement Probability NIPS 2024
Accelerating ERM for data-driven algorithm design using output-sensitive techniques NIPS 2024
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization AISTATS 2024
Is Efficient PAC Learning Possible with an Oracle That Responds "Yes" or "No"? COLT 2024
Scaling laws for learning with real and surrogate data NIPS 2024
The Impact of Differential Privacy on Group Disparity Mitigation NAACL 2024
Majority-of-Three: The Simplest Optimal Learner? COLT 2024
The Price of Implicit Bias in Adversarially Robust Generalization NIPS 2024
Agnostic Multi-Robust Learning using ERM AISTATS 2024
Sharp error bounds for imbalanced classification: how many examples in the minority class? AISTATS 2024
Regularization and Optimal Multiclass Learning COLT 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
On Convex Optimization with Semi-Sensitive Features COLT 2024
Generalized Tensor Decomposition for Understanding Multi-Output Regression under Combinatorial Shifts NIPS 2024
ClusterFix: A Cluster-Based Debiasing Approach Without Protected-Group Supervision WACV 2024
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition JMLR 2024
On the Stability and Generalization of Meta-Learning NIPS 2024
Efficient Algorithms for Learning Monophonic Halfspaces in Graphs COLT 2024
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization NIPS 2024
Label Noise: Ignorance Is Bliss NIPS 2024
Loss-Curvature Matching for Dataset Selection and Condensation AISTATS 2023
A Statistical Perspective on Retrieval-Based Models ICML 2023
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent AISTATS 2023
An Online and Unified Algorithm for Projection Matrix Vector Multiplication with Application to Empirical Risk Minimization AISTATS 2023