2011
NIPS
NeurIPS 2011
On the Universality of Online Mirror Descent
Abstract
We show that for a general class of convex online learning problems, Mirror Descent can always achieve a (nearly) optimal regret guarantee.
🌉
Interdisciplinary Bridge
— Machine Learning and Mathematics & Optimization
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Keyword Pioneer
— online mirror descent
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
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Trend Setter
— Optimization
Authors
Topics
Machine Learning > Optimization & Theory > Learning Theory
Machine Learning > Optimization & Theory > Optimization
Mathematics & Optimization > Optimization
Mathematics & Optimization > Optimization > Online Algorithms
Machine Learning > Learning Types > Online Learning
Mathematics & Optimization > Optimization > Optimization
Machine Learning > Learning Paradigms > Online Learning
Machine Learning > Learning Types > Optimization