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» A regularization framework for multiple-instance learning
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NIPS
2007
13 years 9 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
CVPR
2012
IEEE
11 years 10 months ago
Multi-target tracking by online learning of non-linear motion patterns and robust appearance models
We describe an online approach to learn non-linear motion patterns and robust appearance models for multi-target tracking in a tracklet association framework. Unlike most previous...
Bo Yang, Ram Nevatia
ICDM
2009
IEEE
112views Data Mining» more  ICDM 2009»
14 years 2 months ago
Spatio-temporal Multi-dimensional Relational Framework Trees
—The real world is composed of sets of objects that move and morph in both space and time. Useful concepts can be defined in terms of the complex interactions between the multi-...
Matthew Bodenhamer, Samuel Bleckley, Daniel Fennel...
MM
2006
ACM
152views Multimedia» more  MM 2006»
14 years 1 months ago
Multimodal fusion using learned text concepts for image categorization
Conventional image categorization techniques primarily rely on low-level visual cues. In this paper, we describe a multimodal fusion scheme which improves the image classification...
Qiang Zhu, Mei-Chen Yeh, Kwang-Ting Cheng
ECCV
2008
Springer
14 years 9 months ago
Output Regularized Metric Learning with Side Information
Distance metric learning has been widely investigated in machine learning and information retrieval. In this paper, we study a particular content-based image retrieval application ...
Wei Liu, Steven C. H. Hoi, Jianzhuang Liu