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PAMI
2006
143views more  PAMI 2006»
13 years 10 months ago
Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning
In this paper we present a variational Bayes (VB) framework for learning continuous hidden Markov models (CHMMs), and we examine the VB framework within active learning. Unlike a ...
Shihao Ji, Balaji Krishnapuram, Lawrence Carin
IJCV
2011
264views more  IJCV 2011»
13 years 5 months ago
Cost-Sensitive Active Visual Category Learning
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
Sudheendra Vijayanarasimhan, Kristen Grauman
PAKDD
2011
ACM
473views Data Mining» more  PAKDD 2011»
13 years 3 months ago
 Finding Rare Classes: Adapting Generative and Discriminative Models in Active Learning
Discovering rare categories and classifying new instances of them is an important data mining issue in many fields, but fully supervised learning of a rare class classifier is pr...
Timothy Hospedales, Shaogang Gong and Tao Xiang
ECML
2006
Springer
14 years 1 months ago
Bayesian Active Learning for Sensitivity Analysis
Abstract. Designs of micro electro-mechanical devices need to be robust against fluctuations in mass production. Computer experiments with tens of parameters are used to explore th...
Tobias Pfingsten
IIR
2010
13 years 11 months ago
Sentence-Based Active Learning Strategies for Information Extraction
Given a classifier trained on relatively few training examples, active learning (AL) consists in ranking a set of unlabeled examples in terms of how informative they would be, if ...
Andrea Esuli, Diego Marcheggiani, Fabrizio Sebasti...