Free Downloads Optimization For Machine Learning (Neural Information Processing Series)
The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields.Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.
Series: Neural Information Processing series
Hardcover: 512 pages
Publisher: The MIT Press; 1st edition (September 30, 2011)
Language: English
ISBN-10: 026201646X
ISBN-13: 978-0262016469
Product Dimensions: 8 x 0.9 x 10 inches
Shipping Weight: 2.5 pounds (View shipping rates and policies)
Average Customer Review: Be the first to review this item
Best Sellers Rank: #961,512 in Books (See Top 100 in Books) #143 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Machine Theory #505 in Books > Computers & Technology > Computer Science > Robotics #633 in Books > Computers & Technology > Computer Science > AI & Machine Learning > Intelligence & Semantics
Optimization for Machine Learning (Neural Information Processing series) Learning: 25 Learning Techniques for Accelerated Learning - Learn Faster by 300%! (Learning, Memory Techniques, Accelerated Learning, Memory, E Learning, ... Learning Techniques, Exam Preparation) Bread Machine Cookbook: 101 Delicious, Nutritious, Low Budget, Mouthwatering Bread Machine Cookbook: Best Bread Machine Bread Recipe Recipes for Perfect-Every-Time Bread-From Every Kind of Machine The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning (Information Science and Statistics) Handbook of Neural Networks for Speech Processing (Artech House Signal Processing Library) Machine Learning: An Algorithmic Perspective, Second Edition (Chapman & Hall/Crc Machine Learning & Pattern Recognition) Machine Learning: A Bayesian and Optimization Perspective (Net Developers) Learn: Cognitive Psychology - How to Learn, Any Skill or Subject in 21 Days! (Learn, Learning Disability, Learning Games, Learning Techniques, Learning ... Learning, Cognitive Science, Study) Bread Machine Cooking - The Ultimate Guide to Bread Machine Bread Baking: Over 24 Bread Machine Recipes You Will Love! Conceptual Structures: Information Processing in Mind and Machine (Systems Programming Series) Identification of Nonlinear Systems Using Neural Networks and Polynomial Models: A Block-Oriented Approach (Lecture Notes in Control and Information Sciences) Keyword Research for Search Engine Optimization (2016): Find SEO Keywords That Turns Into a Profitable Money Machine Bayesian Signal Processing: Classical, Modern and Particle Filtering Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control) The Mindful Therapist: A Clinician's Guide to Mindsight and Neural Integration (Norton Series on Interpersonal Neurobiology) From Neural Networks and Biomolecular Engineering to Bioelectronics (Electronics and Biotechnology Advanced (Elba) Forum Series) The Neural Crest (Second Edition) (Developmental and Cell Biology Series) Python : The Ultimate Python Quickstart Guide - From Beginner To Expert (Hands On Projects, Machine Learning, Learn Coding Fast, Learning code, Database) Programming Neural Networks with Encog3 in C# Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets Conversations With Neil's Brain: The Neural Nature Of Thought And Language
