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» Learning aspect models with partially labeled data
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ICML
2003
IEEE
16 years 4 months ago
Learning on the Test Data: Leveraging Unseen Features
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
Benjamin Taskar, Ming Fai Wong, Daphne Koller
SMC
2007
IEEE
120views Control Systems» more  SMC 2007»
15 years 10 months ago
A data-dependent distance measure for transductive instance-based learning
— We consider learning in a transductive setting using instance-based learning (k-NN) and present a method for constructing a data-dependent distance “metric” using both labe...
Jared Lundell, Dan Ventura
JMLR
2012
13 years 6 months ago
Structured Output Learning with High Order Loss Functions
Often when modeling structured domains, it is desirable to leverage information that is not naturally expressed as simply a label. Examples include knowledge about the evaluation ...
Daniel Tarlow, Richard S. Zemel
ISMIS
1999
Springer
15 years 8 months ago
Machine Learning Method for Software Quality Model Building
Software quality prediction can be cast as a concept learning problem. In this paper, we discuss the full cycle of an application of Machine Learning to software quality predictio...
Mauricio Amaral de Almeida, Stan Matwin
SP
2002
IEEE
128views Security Privacy» more  SP 2002»
15 years 3 months ago
Fitting hidden Markov models to psychological data
Markov models have been used extensively in psychology of learning. Applications of hidden Markov models are rare however. This is partially due to the fact that comprehensive stat...
Ingmar Visser, Maartje E. J. Raijmakers, Peter C. ...