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

Distributed Accelerated Proximal Coordinate Gradient Methods IJCAI 2017
Data sparse nonparametric regression with $ε$-insensitive losses ACML 2017
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms ICML 2017
On Optimal Generalizability in Parametric Learning NIPS 2017
Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization NIPS 2017
Algorithmic Stability and Hypothesis Complexity ICML 2017
Efficient Private ERM for Smooth Objectives IJCAI 2017
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization IJCAI 2017
Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM NIPS 2017
First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization NIPS 2017
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization NIPS 2017
On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting JMLR 2016
Learning with Differential Privacy: Stability, Learnability and the Sufficiency and Necessity of ERM Principle JMLR 2016
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics JMLR 2016
Learning Algorithms for Second-Price Auctions with Reserve JMLR 2016
A Convex Surrogate Operator for General Non-Modular Loss Functions AISTATS 2016
A Light Touch for Heavily Constrained SGD COLT 2016
BISTRO: An Efficient Relaxation-Based Method for Contextual Bandits ICML 2016
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization ICML 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling ICML 2016
Variance Reduction for Faster Non-Convex Optimization ICML 2016
Efficient Private Empirical Risk Minimization for High-dimensional Learning ICML 2016
Learnability of Non-I.I.D. ACML 2016
Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers ACML 2016
Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization ACML 2016