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» Learning Algorithms for Domain Adaptation
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ICML
2004
IEEE
16 years 1 months ago
Semi-supervised learning using randomized mincuts
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
Avrim Blum, John D. Lafferty, Mugizi Robert Rweban...
119
Voted
AIME
1997
Springer
15 years 4 months ago
Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods
We used Machine Learning (ML) methods to learn the best decision rules to distinguish normal brain aging from the earliest stages of dementia using subsamples of 198 normal and 244...
William Rodman Shankle, Subramani Mani, Michael J....
CORR
2010
Springer
193views Education» more  CORR 2010»
14 years 11 months ago
A Probabilistic Approach for Learning Folksonomies from Structured Data
Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach t...
Anon Plangprasopchok, Kristina Lerman, Lise Getoor
208
Voted
ICDE
2005
IEEE
120views Database» more  ICDE 2005»
16 years 1 months ago
Corpus-based Schema Matching
Schema Matching is the problem of identifying corresponding elements in different schemas. Discovering these correspondences or matches is inherently difficult to automate. Past s...
Jayant Madhavan, Philip A. Bernstein, AnHai Doan, ...
107
Voted
JAIR
2011
144views more  JAIR 2011»
14 years 7 months ago
Non-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Mahdi Milani Fard, Joelle Pineau