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ICCV
2007
IEEE
14 years 4 months ago
Co-Tracking Using Semi-Supervised Support Vector Machines
This paper treats tracking as a foreground/background classification problem and proposes an online semisupervised learning framework. Initialized with a small number of labeled ...
Feng Tang, Shane Brennan, Qi Zhao, Hai Tao
IUI
2006
ACM
14 years 4 months ago
Are two talking heads better than one?: when should use more than one agent in e-learning?
Recent interest in the use of software character agents raises the issue of how many agents should be used in online learning. In this paper we review evidence concerning the rela...
Hua Wang, Mark H. Chignell, Mitsuru Ishizuka
PKDD
2010
Springer
128views Data Mining» more  PKDD 2010»
13 years 8 months ago
Learning to Tag from Open Vocabulary Labels
Most approaches to classifying media content assume a fixed, closed vocabulary of labels. In contrast, we advocate machine learning approaches which take advantage of the millions...
Edith Law, Burr Settles, Tom M. Mitchell
ECML
2004
Springer
14 years 3 months ago
Learning from Message Pairs for Automatic Email Answering
Abstract. We consider the problem of learning a mapping from question to answer messages. The training data for this problem consist of pairs of messages that have been received an...
Steffen Bickel, Tobias Scheffer
TKDE
2012
226views Formal Methods» more  TKDE 2012»
12 years 15 days ago
DDD: A New Ensemble Approach for Dealing with Concept Drift
—Online learning algorithms often have to operate in the presence of concept drifts. A recent study revealed that different diversity levels in an ensemble of learning machines a...
Leandro L. Minku, Xin Yao