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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression
通信压缩 分布式 随机优化 下界 加速算法
2023/11/29
Communication compression is an essential strategy for alleviating communication overhead by reducing the volume of information exchanged between computing nodes in large-scale distributed stochastic ...
Stochastic Optimization of Floating Point Programs with Tunable Precision
64-bit x86 x86-64, Binary Markov Chain Monte Carlo MCMC Stochastic Search SMT Floating-Point Precision
2016/5/24
The aggressive optimization of floating-point computations is an important problem in high-performance computing. Unfortunately,floating-point instruction sets have complicated semantics that often fo...
Disciplined convex stochastic programming: A new framework for stochastic optimization
Convex stochastic programming modeling mathematics DCSP modeling
2015/8/7
We introduce disciplined convex stochastic programming (DCSP), a modeling framework that can significantly lower the barrier for modelers to specify and solve convex stochastic optimization problems, ...
This paper is concerned with the use of grid search as a means of optimizaing an objective function that can be evaluated only through simulation. We study the question of how rapidly the number of re...
Spectral Risk Measures, With Adaptions For Stochastic Optimization
Spectral Risk Measures Adaptions Stochastic Optimization
2012/11/22
Stochastic optimization problems often involve the expectation in its objective. When risk is incorporated in the problem description as well, then risk measures have to be involved in addition to qua...
LIBRJMCMC: AN OPEN-SOURCE GENERIC C++ LIBRARY FOR STOCHASTIC OPTIMIZATION
Stochastic Optimization RJ-MCMC Simulated Annealing Generic C++ Library Open-Source
2014/4/28
The librjmcmc is an open source C++ library that solves optimization problems using a stochastic framework. The library is primarily intended for but not limited to research purposes in computer visio...
Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions
Stochastic optimization sparse statistical recovery optimal algorithm high dimensions
2012/9/19
We develop and analyze stochastic optimization algorithms for problems in which the ex-pected loss is strongly convex, and the optimum is (approximately)sparse. Previous approaches are able to exploit...
Sequence alignment from the perspective of stochastic optimization: a survey
Sequence alignment stochastic optimization simulated annealing genetic algorithms particle swarm optimization ant colonyoptimization
2011/3/22
DNA and protein are the fundamental biological sequences. DNA is a fundamental molecule that plays a vital role in the processes of life. Proteins synthesized by DNA in a cell are the building blocks ...
An application of stochastic optimization theory to institutional finance
Depository Financial Institutions Stochastic Modeling
2010/9/15
A current problem in institutional finance is to devise a means of computing the maximum profit that can be made by a depository financial institution (DFI). Such institutions are characterized by the...