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large-scale optimization

27 papers

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convex optimization (1320) stochastic optimization (1060) matrix factorization (529) empirical risk minimization (348) newton method (64) stochastic gradient descent (1088) distributed optimization (275) hessian approximation (40) nonsmooth optimization (49) optimization algorithm (148)

Papers

Sketched Newton Value Iteration for Large-Scale Markov Decision Processes AAAI 2024
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems NIPS 2024
Transition-Informed Reinforcement Learning for Large-Scale Stackelberg Mean-Field Games AAAI 2024
Adaptive Constraint Partition Based Optimization Framework for Large-Scale Integer Linear Programming (Student Abstract) AAAI 2023
Parallel Index-Based Search Algorithm for Coalition Structure Generation (Student Abstract) AAAI 2023
Simulation-Assisted Optimization for Large-Scale Evacuation Planning with Congestion-Dependent Delays IJCAI 2023
On Constraints in First-Order Optimization: A View from Non-Smooth Dynamical Systems JMLR 2022
ECLIPSE: An Extreme-Scale Linear Program Solver for Web-Applications ICML 2020
Estimating the Error of Randomized Newton Methods: A Bootstrap Approach ICML 2020
Scalable Approximations for Generalized Linear Problems JMLR 2019
Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models IJCAI 2018
Cut-Pursuit Algorithm for Regularizing Nonsmooth Functionals with Graph Total Variation ICML 2018
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method AISTATS 2018
A Study on Trust Region Update Rules in Newton Methods for Large-scale Linear Classification ACML 2017
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models AISTATS 2016
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk NIPS 2015
Large-scale L-BFGS using MapReduce NIPS 2014
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods ICML 2014
A Reliable Effective Terascale Linear Learning System JMLR 2014
Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization NIPS 2013
Scalable nonconvex inexact proximal splitting NIPS 2012
Stochastic Gradient Descent with Only One Projection NIPS 2012
Practical Large-Scale Optimization for Max-norm Regularization NIPS 2010
Decomposing Isotonic Regression for Efficiently Solving Large Problems NIPS 2010
Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization JMLR 2009