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A Smoothing Direct Search Method for Monte Carlo-Based Bound Constrained Composite Nonsmooth Optimization

  • Published:2018-01 Issue:4 Volume:40 Page:A2174-A2199
  • ISSN:1064-8275
  • Container-title:SIAM Journal on Scientific Computing
  • language:en
  • Short-container-title:SIAM J. Sci. Comput.

Author:

Chen Xiaojun,Kelley C. T.ORCID,Xu Fengmin,Zhang Zaikun

Funder

Army Research Office

Hong Kong Polytechnic University

National Natural Science Foundation of China

National Science Foundation

Research Grants Council, University Grants Committee

U.S. Department of Energy

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Computational Mathematics

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1. Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization;Mathematical Programming Computation;2023-03-14

2. Smoothing Accelerated Proximal Gradient Method with Fast Convergence Rate for Nonsmooth Convex Optimization Beyond Differentiability;Journal of Optimization Theory and Applications;2023-03-04

3. A bi-level optimization approach for portfolio problems with cardinality constraints;2022 18th International Conference on Computational Intelligence and Security (CIS);2022-12

4. Optimization of Stochastic Blackboxes with Adaptive Precision;SIAM Journal on Optimization;2021-01

5. Two decades of blackbox optimization applications;EURO Journal on Computational Optimization;2021
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