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» A Framework for Multiple-Instance Learning
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97
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NIPS
2004
15 years 4 months ago
Unsupervised Variational Bayesian Learning of Nonlinear Models
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Antti Honkela, Harri Valpola
113
Voted
CIDU
2010
15 years 19 days ago
Improving Cause Detection Systems with Active Learning
Active learning has been successfully applied to many natural language processing tasks for obtaining annotated data in a cost-effective manner. We propose several extensions to an...
Isaac Persing, Vincent Ng
94
Voted
ICASSP
2011
IEEE
14 years 6 months ago
Joint dictionary learning and topic modeling for image clustering
A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
131
Voted
ICDM
2008
IEEE
97views Data Mining» more  ICDM 2008»
15 years 9 months ago
Semi-supervised Learning from General Unlabeled Data
We consider the problem of Semi-supervised Learning (SSL) from general unlabeled data, which may contain irrelevant samples. Within the binary setting, our model manages to better...
Kaizhu Huang, Zenglin Xu, Irwin King, Michael R. L...
137
Voted
JCP
2007
105views more  JCP 2007»
15 years 2 months ago
Intuitive Network Applications: Learning for Personalized Converged Services Involving Social Networks
Abstract— The convergence of the wireline telecom, wireless telecom, and internet networks and the services they provide offers tremendous opportunities in services personalizati...
Robert Dinoff, Tin Kam Ho, Richard Hull, Bharat Ku...