
SGDLibrary: A MATLAB library for stochastic gradient descent algorithms
We consider the problem of finding the minimizer of a function f: R^d →R...
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Randomized Iterative Methods for Linear Systems: Momentum, Inexactness and Gossip
In the era of big data, one of the key challenges is the development of ...
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Thirdorder Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima
We propose stochastic optimization algorithms that can find local minima...
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Learning to Optimize Neural Nets
Learning to Optimize is a recently proposed framework for learning optim...
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DeepLearningEnabled Simulated Annealing for Topology Optimization
Topology optimization by distributing materials in a domain requires sto...
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BrainLike Stochastic Search: A Research Challenge and Funding Opportunity
BrainLike Stochastic Search (BLiSS) refers to this task: given a family...
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Metaheuristic Optimization: Algorithm Analysis and Open Problems
Metaheuristic algorithms are becoming an important part of modern optimi...
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A Note On The Popularity of Stochastic Optimization Algorithms in Different Fields: A Quantitative Analysis from 2007 to 2017
Stochastic optimization algorithms are often used to solve complex largescale optimization problems in various fields. To date, there have been a number of stochastic optimization algorithms such as Genetic Algorithm, Cuckoo Search, Tabu Search, Simulated Annealing, Particle Swarm Optimization, Ant Colony Optimization, etc. Each algorithm has some advantages and disadvantages. Currently, there is no study that can help researchers to choose the most popular optimization algorithm to deal with the problems in different research fields. In this note, a quantitative analysis of the popularity of 14 stochastic optimization algorithms in 18 different research fields in the last ten years from 2007 to 2017 is provided. This quantitative analysis can help researchers/practitioners select the best optimization algorithm to solve complex largescale optimization problems in the fields of Engineering, Computer science, Operations research, Mathematics, Physics, Chemistry, Automation control systems, Materials science, Energy fuels, Mechanics, Telecommunications, Thermodynamics, Optics, Environmental sciences ecology, Water resources, Transportation, Construction building technology, and Robotics.
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