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NIPS
2000
13 years 9 months ago
Active Learning for Parameter Estimation in Bayesian Networks
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Simon Tong, Daphne Koller
ICML
2005
IEEE
14 years 8 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
PRL
2008
97views more  PRL 2008»
13 years 7 months ago
Repairing self-confident active-transductive learners using systematic exploration
We consider an active learning game within a transductive learning model. A major problem with many active learning algorithms is that an unreliable current hypothesis can mislead...
Ron Begleiter, Ran El-Yaniv, Dmitry Pechyony
NIPS
2008
13 years 9 months ago
Human Active Learning
We investigate a topic at the interface of machine learning and cognitive science. Human active learning, where learners can actively query the world for information, is contraste...
Rui M. Castro, Charles Kalish, Robert Nowak, Ruich...
SIGIR
2012
ACM
11 years 10 months ago
Active query selection for learning rankers
Methods that reduce the amount of labeled data needed for training have focused more on selecting which documents to label than on which queries should be labeled. One exception t...
Mustafa Bilgic, Paul N. Bennett