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» An Instance Selection Approach to Multiple Instance Learning
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PKDD
2009
Springer
134views Data Mining» more  PKDD 2009»
14 years 3 months ago
Multi-task Feature Selection Using the Multiple Inclusion Criterion (MIC)
Abstract. We address the problem of joint feature selection in multiple related classification or regression tasks. When doing feature selection with multiple tasks, usually one c...
Paramveer S. Dhillon, Brian Tomasik, Dean P. Foste...
ICCV
2009
IEEE
15 years 1 months ago
Joint learning of visual attributes, object classes and visual saliency
We present a method to learn visual attributes (eg.“red”, “metal”, “spotted”) and object classes (eg. “car”, “dress”, “umbrella”) together. We assume imag...
Gang Wang, David Forsyth
ICML
2009
IEEE
14 years 9 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
ECML
2005
Springer
14 years 2 months ago
Estimation of Mixture Models Using Co-EM
We study estimation of mixture models for problems in which multiple views of the instances are available. Examples of this setting include clustering web pages or research papers ...
Steffen Bickel, Tobias Scheffer
ICASSP
2010
IEEE
13 years 9 months ago
Detecting local semantic concepts in environmental sounds using Markov model based clustering
Detecting the time of occurrence of an acoustic event (for instance, a cheer) embedded in a longer soundtrack is useful and important for applications such as search and retrieval...
Keansub Lee, Daniel P. W. Ellis, Alexander C. Loui