empirical risk minimization

First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization NeurIPS 2017 Multi-Observation Elicitation COLT 2017 On Optimal Generalizability in Parametric Learning NeurIPS 2017 On the Fine-Grained Complexity of Empirical Risk Minimization: Kernel Methods and Neural Networks NeurIPS 2017 Regularization and the small-ball method II: complexity dependent error rates JMLR 2017 Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization JMLR 2017 A Convex Surrogate Operator for General Non-Modular Loss Functions AISTATS 2016 Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NeurIPS 2016 A Light Touch for Heavily Constrained SGD COLT 2016 A Simple Practical Accelerated Method for Finite Sums NeurIPS 2016 BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits ICML 2016 Efficient Private Empirical Risk Minimization for High-dimensional Learning ICML 2016 Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling ICML 2016 Exploiting the Structure: Stochastic Gradient Methods Using Raw Clusters NeurIPS 2016 Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back NeurIPS 2016 Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than O(1/ε) NeurIPS 2016 Learnability of Non-I.I.D. ACML 2016 Learning Algorithms for Second-Price Auctions with Reserve JMLR 2016 Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers ACML 2016 Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle JMLR 2016 On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability NeurIPS 2016 On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting JMLR 2016 Open Problem: Property Elicitation and Elicitation Complexity COLT 2016 Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics JMLR 2016 SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization ICML 2016