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math.OCJun 12, 2010
17
citations (OpenAlex)
authors
  • Elad Hazan
  • Satyen Kale
arXiv abstractPDF
paper

An optimal algorithm for stochastic strongly-convex optimization

arXiv:1006.2425

Abstract

We consider stochastic convex optimization with a strongly convex (but not necessarily smooth) objective. We give an algorithm which performs only gradient updates with optimal rate of convergence.

Cited by in corpus (8)

  • Stochastic (Approximate) Proximal Point Methods: Convergence, Optimality, and Adaptivity
  • Asynchronous stochastic convex optimization
  • On the Adaptivity of Stochastic Gradient-Based Optimization
  • Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization
  • Large Scale Markov Decision Processes with Changing Rewards
  • Adapting to Function Difficulty and Growth Conditions in Private Optimization
  • On Misspecification in Prediction Problems and Robustness via Improper Learning
  • Greedy Step Averaging: A parameter-free stochastic optimization method
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