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IJCAI
2001
15 years 9 months ago
Active Learning for Structure in Bayesian Networks
The task of causal structure discovery from empirical data is a fundamental problem in many areas. Experimental data is crucial for accomplishing this task. However, experiments a...
Simon Tong, Daphne Koller
NIPS
2000
15 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
ICIP
2006
IEEE
16 years 9 months ago
Precision-Oriented Active Selection for Interactive Image Retrieval
Active learning methods have been considered with an increased interest in the content-based image retrieval (CBIR) community. Those methods used to be based on classical classifi...
Philippe Henri Gosselin, Matthieu Cord
HT
2009
ACM
16 years 8 days ago
Modeling and predicting group activity over time in online social media
This paper develops a probabilistic framework that can model and predict group activity over time on online social media. Users of social media sites such as Flickr often face the...
Munmun De Choudhury
DIS
2008
Springer
15 years 9 months ago
Active Learning for High Throughput Screening
Abstract. An important task in many scientific and engineering disciplines is to set up experiments with the goal of finding the best instances (substances, compositions, designs) ...
Kurt De Grave, Jan Ramon, Luc De Raedt