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» An Application Framework for Collaborative Learning
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135
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CORR
2004
Springer
140views Education» more  CORR 2004»
15 years 3 months ago
Integrating Defeasible Argumentation and Machine Learning Techniques
The field of machine learning (ML) is concerned with the question of how to construct algorithms that automatically improve with experience. In recent years many successful ML app...
Sergio Alejandro Gómez, Carlos Iván ...
127
Voted
MICCAI
2010
Springer
15 years 2 months ago
Agreement-Based Semi-supervised Learning for Skull Stripping
Abstract. Learning-based approaches have become increasingly practical in medical imaging. For a supervised learning strategy, the quality of the trained algorithm (usually a class...
Juan Eugenio Iglesias, Cheng-Yi Liu, Paul M. Thomp...
133
Voted
JMLR
2010
154views more  JMLR 2010»
14 years 10 months ago
Infinite Predictor Subspace Models for Multitask Learning
Given several related learning tasks, we propose a nonparametric Bayesian model that captures task relatedness by assuming that the task parameters (i.e., predictors) share a late...
Piyush Rai, Hal Daumé III
164
Voted
AAAI
2011
14 years 3 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
138
Voted
FLAIRS
2007
15 years 6 months ago
Explaining Task Processing in Cognitive Assistants that Learn
As personal assistant software matures and assumes more autonomous control of its users’ activities, it becomes more critical that this software can explain its task processing....
Deborah L. McGuinness, Alyssa Glass, Michael Wolve...