conftrace_
← Back to papers
2012 NIPS NeurIPS 2012

Proximal Newton-type methods for convex optimization

Abstract

We seek to solve convex optimization problems in composite form:

🌉 Interdisciplinary Bridge - Machine Learning and Mathematics & Optimization
🧭 Keyword Pioneer - proximal newton methods
🐝 Cross-Pollinator - Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy
📈 Trend Setter - Optimization

Authors

Jason Lee , Yuekai Sun , Michael Saunders

Topics

Machine Learning > Optimization & Theory > Optimization Mathematics & Optimization > Optimization > Continuous Optimization Deep Learning > Optimization & Theory > Optimization Mathematics & Optimization > Optimization > Convex Optimization

Keywords

convex optimization composite optimization proximal newton methods first-order method newton-type method proximal method second order cone program
Download PDF

Related papers

Kernel Hyperalignment 2012
Fused sparsity and robust estimation for linear models with unknown variance 2012
Slice sampling normalized kernel-weighted completely random measure mixture models 2012
Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization 2012
Matrix reconstruction with the local max norm 2012