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» Multiple instance learning for sparse positive bags
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CVPR
2011
IEEE
13 years 3 months ago
FlowBoost - Appearance Learning from Sparsely Annotated Video
We propose a new learning method which exploits temporal consistency to successfully learn a complex appearance model from a sparsely labeled training video. Our approach consists...
Karim Ali, Francois Fleuret, David Hasler
PKDD
2010
Springer
158views Data Mining» more  PKDD 2010»
13 years 6 months ago
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...
Katya Scheinberg, Irina Rish
PR
2007
133views more  PR 2007»
13 years 7 months ago
Incorporating multiple SVMs for automatic image annotation
In this paper, a novel automatic image annotation system is proposed, which integrates two sets of support vector machines (SVMs), namely the multiple instance learning (MIL)-base...
Xiaojun Qi, Yutao Han
ICML
2009
IEEE
13 years 5 months ago
Multiple indefinite kernel learning with mixed norm regularization
We address the problem of learning classifiers using several kernel functions. On the contrary to many contributions in the field of learning from different sources of information...
Matthieu Kowalski, Marie Szafranski, Liva Ralaivol...
ICDM
2009
IEEE
199views Data Mining» more  ICDM 2009»
14 years 2 months ago
Active Learning with Adaptive Heterogeneous Ensembles
—One common approach to active learning is to iteratively train a single classifier by choosing data points based on its uncertainty, but it is nontrivial to design uncertainty ...
Zhenyu Lu, Xindong Wu, Josh Bongard