1393 search results - page 13 / 279 » Machine Learning by Function Decomposition |
ICML
2009
IEEE
16 years 17 days ago
2009
IEEE
This paper addresses the problem of approximate singular value decomposition of large dense matrices that arises naturally in many machine learning applications. We discuss two re...
ICML
2009
IEEE
16 years 17 days ago
2009
IEEE
We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
COLT
2007
Springer
15 years 6 months ago
2007
Springer
We present data-dependent error bounds for transductive learning based on transductive Rademacher complexity. For specific algorithms we provide bounds on their Rademacher complex...
WFLP
2000
Springer
15 years 3 months ago
2000
Springer
Abstract. Traditionally, machine learning algorithms such as decision tree learners have employed attribute-value representations. From the early 80's on people have started t...
ICML
2005
IEEE
16 years 16 days ago
2005
IEEE
We present Variable Influence Structure Analysis, an algorithm that dynamically performs hierarchical decomposition of factored Markov decision processes. Our algorithm determines...