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» Tracking the Invisible: Learning Where the Object Might be
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CVPR
2010
IEEE
15 years 5 months ago
Online Multiple Instance Learning with No Regret
Multiple instance (MI) learning is a recent learning paradigm that is more flexible than standard supervised learning algorithms in the handling of label ambiguity. It has been u...
Li Mu, James Kwok, Lu Bao-liang
IJCAI
1997
14 years 11 months ago
Mental Tracking: A Computational Model of Spatial Development
Psychological experiments on children's development of spatial knowledge suggest experience at self-locomotion with visual tracking as important factors. Yet, the mechanism u...
Kazuo Hiraki, Akio Sashima, Steven Phillips
NIPS
2004
14 years 11 months ago
Object Classification from a Single Example Utilizing Class Relevance Metrics
We describe a framework for learning an object classifier from a single example. This goal is achieved by emphasizing the relevant dimensions for classification using available ex...
Michael Fink 0002
JMLR
2012
13 years 2 days ago
Domain Adaptation: A Small Sample Statistical Approach
We study the prevalent problem when a test distribution differs from the training distribution. We consider a setting where our training set consists of a small number of sample d...
Ruslan Salakhutdinov, Sham M. Kakade, Dean P. Fost...
CLOR
2006
15 years 1 months ago
Sequential Learning of Layered Models from Video
Abstract. A popular framework for the interpretation of image sequences is the layers or sprite model, see e.g. [1], [2]. Jojic and Frey [3] provide a generative probabilistic mode...
Michalis K. Titsias, Christopher K. I. Williams