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NIPS
1998
13 years 10 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
ECML
2006
Springer
14 years 22 days ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...
RA
2003
135views Robotics» more  RA 2003»
13 years 10 months ago
Behavioural Cloning and Robot Control
Behavioural cloning is a method by which a machine learns control skills through observing what a human controller would do in a certain set of circumstances. More specifically, t...
Claire D'Este, Mark O'Sullivan, Nicholas Hannah
JMLR
2010
125views more  JMLR 2010»
13 years 3 months ago
On utility of gene set signatures in gene expression-based cancer class prediction
Machine learning methods that can use additional knowledge in their inference process are central to the development of integrative bioinformatics. Inclusion of background knowled...
Minca Mramor, Marko Toplak, Gregor Leban, Tomaz Cu...
ICML
2005
IEEE
14 years 10 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore