Everything old is new again : a fresh look at historical approaches in machine learning
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2002. === Includes bibliographical references (leaves 213-225). === This thesis shows that several old, somewhat discredited machine learning techniques are still valuable in the solution of modern, large-scale machi...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | English |
| Published: |
Massachusetts Institute of Technology
2005
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/17549 |