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COLT
2005
Springer
14 years 2 months ago
Analysis of Perceptron-Based Active Learning
We start by showing that in an active learning setting, the Perceptron algorithm needs Ω( 1 ε2 ) labels to learn linear separators within generalization error ε. We then prese...
Sanjoy Dasgupta, Adam Tauman Kalai, Claire Montele...
CORR
2011
Springer
219views Education» more  CORR 2011»
13 years 3 months ago
Active Markov Information-Theoretic Path Planning for Robotic Environmental Sensing
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...
Kian Hsiang Low, John M. Dolan, Pradeep K. Khosla
IDA
2006
Springer
13 years 8 months ago
Backward chaining rule induction
Exploring the vast number of possible feature interactions in domains such as gene expression microarray data is an onerous task. We describe Backward-Chaining Rule Induction (BCR...
Douglas H. Fisher, Mary E. Edgerton, Zhihua Chen, ...
FLAIRS
2009
13 years 6 months ago
Lifting the Limitations in a Rule-based Policy Language
The predicates that are used to encode a planning domain in PDDL often do not include concepts that are important for effectively reasoning about problems in the domain. In partic...
Alan Lindsay, Maria Fox, Derek Long
LWA
2008
13 years 10 months ago
Hybrid Personalization For Recommendations
In this paper we present the concept of hybrid personalization, the combination of multiple atomic personalization mechanisms. The idea of hybrid personalization is related to hyb...
Eelco Herder, Philipp Kärger