Learning with kernels :support vector machines, regularization, optimization,…

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by…

Learning kernel classifiers :theory and algorithms

Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier--a limited, but well-established and comprehensively studied model--and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence analysis. This…

The rapid evaluation of potential fields in particle systems

"Leslie Greengard received his doctorate from Yale University where he is a NSF Postdoctoral Fellow in the Computer Science Department. The Rapid Evaluation of Potential Fields in Particle Systems is a 1987 ACM Distinguished Dissertation.""The Rapid Evaluation of Potential Fields in Particle Systems presents a group of algorithms for the computation of the potential and force fields in large-sc…

Self-stabilization

OCLC-licensed vendor bibliographic record.

WALCOM: Algorithms and Computation 9th International Workshop, WALCOM 2015, …

This book constitutes the thoroughly refereed conference proceedings of the 9th International Workshop on Algorithms and Computation, WALCOM 2015, held in Dhaka, Bangladesh, in February 2015. The 26 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 85 submissions. The papers are organized in topical sections on approximation algorithms, data s…

A Comparison Study of PAPR Reduction in OFDM Systems Based on Swarm Intellige…