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» Learn .MT: A New Approach to Incremental Learning
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ALT
2010
Springer
15 years 7 months ago
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Rong Jin, Steven C. H. Hoi, Tianbao Yang
KDD
1995
ACM
148views Data Mining» more  KDD 1995»
15 years 9 months ago
Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
Philip K. Chan, Salvatore J. Stolfo
ICML
2000
IEEE
16 years 7 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
ICMLA
2009
15 years 4 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
EXACT
2007
15 years 8 months ago
Learning Models from Temporal-Logic Properties via Explanations
Given a model and a property expressed in temporal logic, a model checker normally produces a counterexample in case the model does not satisfy the property. This counterexample i...
Miguel A. Carrillo, David A. Rosenblueth