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Escaping the Local Minima via Simulated Annealing: Optimization of
  Approximately Convex Functions

Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions

28 January 2015
A. Belloni
Tengyuan Liang
Hariharan Narayanan
Alexander Rakhlin
ArXivPDFHTML

Papers citing "Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions"

4 / 4 papers shown
Title
On Zeroth-Order Stochastic Convex Optimization via Random Walks
On Zeroth-Order Stochastic Convex Optimization via Random Walks
Tengyuan Liang
Hariharan Narayanan
Alexander Rakhlin
52
24
0
11 Feb 2014
On the Complexity of Bandit and Derivative-Free Stochastic Convex
  Optimization
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization
Ohad Shamir
208
191
0
11 Sep 2012
Stochastic convex optimization with bandit feedback
Stochastic convex optimization with bandit feedback
Alekh Agarwal
Dean Phillips Foster
Daniel J. Hsu
Sham Kakade
Alexander Rakhlin
109
239
0
08 Jul 2011
On the Computational Complexity of MCMC-based Estimators in Large
  Samples
On the Computational Complexity of MCMC-based Estimators in Large Samples
A. Belloni
Victor Chernozhukov
306
96
0
17 Apr 2007
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