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NIPS
2004
13 years 8 months ago
Analysis of a greedy active learning strategy
act out the core search problem of active learning schemes, to better understand the extent to which adaptive labeling can improve sample complexity. We give various upper and low...
Sanjoy Dasgupta
JODL
2008
175views more  JODL 2008»
13 years 7 months ago
ALOCOM: a generic content model for learning objects
e-Learning organizations are focusing heavily on learning content reusability. The ultimate objective is a learning object economy characterized by searchable digital libraries of ...
Katrien Verbert, Erik Duval
JMLR
2011
111views more  JMLR 2011»
13 years 2 months ago
Models of Cooperative Teaching and Learning
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
PROMISE
2010
13 years 2 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
ICML
2006
IEEE
14 years 8 months ago
Learning low-rank kernel matrices
Kernel learning plays an important role in many machine learning tasks. However, algorithms for learning a kernel matrix often scale poorly, with running times that are cubic in t...
Brian Kulis, Inderjit S. Dhillon, Máty&aacu...