Stochastic Optimization Methods For Modern Machine Learning Problems

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Stochastic Optimization Methods For Modern Machine Learning Problems

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Author : Yuejiao Sun
language : en
Publisher:
Release Date : 2021

Stochastic Optimization Methods For Modern Machine Learning Problems written by Yuejiao Sun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.

Optimization has been the workhorse of solving machine learning problems. However, the efficiency of these methods remains far from satisfaction to meet the ever-growing demand that arises in modern applications. In this context, the present dissertation will focus on two fundamental classes of machine learning problems: 1) stochastic nested problems, where one subproblem builds upon the solution of others; and, 2) stochastic distributed problems, where the subproblems are coupled through sharing the common variables. One key difficulty of solving stochastic nested problems is that the hierarchically coupled structure makes the computation of (stochastic) gradients, the basic element in first-order optimization machinery, prohibitively expensive or even impossible.We will develop the first stochastic optimization method, which runs in a single-loop manner and achieves the same sample complexity as the stochastic gradient descent method for non-nested problems. One key difficulty of solving stochastic distributed problems is the resource intensity, especially when algorithms are running atresource-limited devices. In this context, we will introduce a class of communication-adaptive stochastic gradient descent (SGD) methods, which adaptively reuse the stale gradients, thus saving communication. We will show that the new algorithms have convergence rates comparable to original SGD and Adam algorithms, but enjoy impressive empirical performance in terms of total communication round reduction.

Proceedings Of The Twenty Second Aaai Conference On Artificial Intelligence

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Author :
language : en
Publisher:
Release Date : 2007

Proceedings Of The Twenty Second Aaai Conference On Artificial Intelligence written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Artificial intelligence categories.

Modern Heuristic Search Methods

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Author : V. J. Rayward-Smith
language : en
Publisher: John Wiley & Sons
Release Date : 1996-12-23

Modern Heuristic Search Methods written by V. J. Rayward-Smith and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-12-23 with Computers categories.

Including contributions from leading experts in the field, this book covers applications and developments of heuristic search methods for solving complex optimization problems. The book covers various local search strategies including genetic algorithms, simulated annealing, tabu search and hybrids thereof. These methods have proved extraordinarily successful by solving some of the most difficult, real-world problems. At the interface between Artificial Intelligence and Operational Research, research in this exciting area is progressing apace spurred on by the needs of industry and commerce. The introductory chapter provides a clear overview of the basic techniques and useful pointers to further reading and to current research. The second section of the book covers some of the most recent and exciting developments of the basic techniques, with suggestions not only for extending and improving these but also for hybridizing and incorporating automatic adaption. The third section contains a number of case studies, surveys and comparative studies which span a wide range of application areas ranging from the classic Steiner tree problem to more practical problems arising in telecommunications and data analysis. The coverage of the latest research and the illustrative case studies will ensure that the book is invaluable for researchers and professionals with an interest in heuristic search methods.

Informs Annual Meeting

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Author : Institute for Operations Research and the Management Sciences. National Meeting
language : en
Publisher:
Release Date : 2009

Informs Annual Meeting written by Institute for Operations Research and the Management Sciences. National Meeting and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Industrial management categories.

The Cross Entropy Method For Combinatorial Optimization Rare Event Simulation And Neural Computation

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Author :
language : en
Publisher:
Release Date : 2005

The Cross Entropy Method For Combinatorial Optimization Rare Event Simulation And Neural Computation written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Combinatorial optimization categories.

Gradient Descent Stochastic Optimization And Other Tales

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Author : Jun Lu
language : en
Publisher: Eliva Press
Release Date : 2022-07-22

Gradient Descent Stochastic Optimization And Other Tales written by Jun Lu and has been published by Eliva Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-22 with categories.

The goal of this book is to debunk and dispel the magic behind the black-box optimizers and stochastic optimizers. It aims to build a solid foundation on how and why the techniques work. This manuscript crystallizes this knowledge by deriving from simple intuitions, the mathematics behind the strategies. This book doesn't shy away from addressing both the formal and informal aspects of gradient descent and stochastic optimization methods. By doing so, it hopes to provide readers with a deeper understanding of these techniques as well as the when, the how and the why of applying these algorithms. Gradient descent is one of the most popular algorithms to perform optimization and by far the most common way to optimize machine learning tasks. Its stochastic version receives attention in recent years, and this is particularly true for optimizing deep neural networks. In deep neural networks, the gradient followed by a single sample or a batch of samples is employed to save computational resources and escape from saddle points. In 1951, Robbins and Monro published A stochastic approximation method, one of the first modern treatments on stochastic optimization that estimates local gradients with a new batch of samples. And now, stochastic optimization has become a core technology in machine learning, largely due to the development of the back propagation algorithm in fitting a neural network. The sole aim of this article is to give a self-contained introduction to concepts and mathematical tools in gradient descent and stochastic optimization.

Proceedings Of The 21st International Conference On Power Industry Computer Applications

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Author : IEEE Power Engineering Society
language : en
Publisher:
Release Date : 1999

Proceedings Of The 21st International Conference On Power Industry Computer Applications written by IEEE Power Engineering Society and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.

"IEEE Catalog Number 99CH36351"--verso of T.p.

36th Aerospace Sciences Meeting Exhibit

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Author :
language : en
Publisher:
Release Date : 1998

36th Aerospace Sciences Meeting Exhibit written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Aeronautics categories.

Evolutionary Algorithms And Intelligent Tools In Engineering Optimization

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Author : William Annicchiarico
language : en
Publisher: WIT Press (UK)
Release Date : 2005

Evolutionary Algorithms And Intelligent Tools In Engineering Optimization written by William Annicchiarico and has been published by WIT Press (UK) this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.

Evolutionary algorithms are very powerful techniques used to find solutions to real-world search and optimisation problems. In this text, a large spectrum of innovative evolutionary and intelligence methods are presented and used for solving various application problems.

Peterson S Graduate And Professional Programs

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Author : Peterson's Guides Staff
language : en
Publisher: Peterson Nelnet Company
Release Date : 2006-12-17

Peterson S Graduate And Professional Programs written by Peterson's Guides Staff and has been published by Peterson Nelnet Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-17 with Education categories.

A basic listing of all accredited graduate programs at universitites in the U.S and Canada.