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» Learning Algorithms for Domain Adaptation
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KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 26 days ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin
ECML
2006
Springer
15 years 4 months ago
Sequence Discrimination Using Phase-Type Distributions
Abstract We propose in this paper a novel approach to the classification of discrete sequences. This approach builds a model fitting some dynamical features deduced from the learni...
Jérôme Callut, Pierre Dupont
104
Voted
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 17 days ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
JAIR
2011
134views more  JAIR 2011»
14 years 7 months ago
Scaling up Heuristic Planning with Relational Decision Trees
Current evaluation functions for heuristic planning are expensive to compute. In numerous planning problems these functions provide good guidance to the solution, so they are wort...
Tomás de la Rosa, Sergio Jiménez, Ra...
86
Voted
STOC
2003
ACM
102views Algorithms» more  STOC 2003»
16 years 23 days ago
Some 3CNF properties are hard to test
For a Boolean formula on n variables, the associated property P is the collection of n-bit strings that satisfy . We study the query complexity of tests that distinguish (with hig...
Eli Ben-Sasson, Prahladh Harsha, Sofya Raskhodniko...