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ICML
2007
IEEE
14 years 11 months ago
Large-scale RLSC learning without agony
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
Wenye Li, Kin-Hong Lee, Kwong-Sak Leung
SMC
2007
IEEE
14 years 4 months ago
Enhancing embodied evolution with punctuated anytime learning
—This paper discusses a new implementation of embodied evolution that uses the concept of punctuated anytime learning to increase the complexity of tasks that the learning system...
Gary B. Parker, Gregory E. Fedynyshyn
ACML
2009
Springer
14 years 2 months ago
Max-margin Multiple-Instance Learning via Semidefinite Programming
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...
Yuhong Guo
APIN
2004
81views more  APIN 2004»
13 years 10 months ago
Learning Generalized Policies from Planning Examples Using Concept Languages
In this paper we are concerned with the problem of learning how to solve planning problems in one domain given a number of solved instances. This problem is formulated as the probl...
Mario Martin, Hector Geffner
ECML
2005
Springer
14 years 3 months ago
Machine Learning of Plan Robustness Knowledge About Instances
Abstract. Classical planning domain representations assume all the objects from one type are exactly the same. But when solving problems in the real world systems, the execution of...
Sergio Jiménez, Fernando Fernández, ...