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» Learning from Ambiguously Labeled Examples
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ICCV
2009
IEEE
15 years 4 months ago
Correlated Probabilistic Trajectories for Pedestrian Motion Detection
This paper introduces an algorithm for detecting walking motion using point trajectories in video sequences. Given a number of point trajectories, we identify those which are sp...
Frank Perbet, Atsuto Maki, Bjorn Stenger
IJCAI
2003
14 years 10 days ago
Integrating Background Knowledge Into Text Classification
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Sarah Zelikovitz, Haym Hirsh
CVPR
2012
IEEE
12 years 1 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
ISMIS
1999
Springer
14 years 3 months ago
Machine Learning Method for Software Quality Model Building
Software quality prediction can be cast as a concept learning problem. In this paper, we discuss the full cycle of an application of Machine Learning to software quality predictio...
Mauricio Amaral de Almeida, Stan Matwin
ICML
2006
IEEE
14 years 11 months ago
Combining discriminative features to infer complex trajectories
We propose a new model for the probabilistic estimation of continuous state variables from a sequence of observations, such as tracking the position of an object in video. This ma...
David A. Ross, Simon Osindero, Richard S. Zemel