Distributed Optimization and Statistical Learning Via the Alternating Direction Method of Multipliers

by Borja Peleato, Stephen Boyd, Neal Parikh, et al.

Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a very large number of features or training examples. As a result, both the decentralized collection or storage of these datasets as well as accompanying distributed solution methods are either necessary...

• Format: Paperback
• Language: English
• ISBN: 160198460X
• ISBN13: 9781601984609
• Release Date: June 2011
• Publisher: Now Publishers
• Length: 140 Pages
• Weight: 0.45 lbs.
• Dimensions: 0.3" x 6.1" x 9.2"