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AI
2010
Springer
13 years 7 months ago
Learning conditional preference networks
We investigate the problem of eliciting CP-nets in the well-known model of exact learning with equivalence and membership queries. The goal is to identify a preference ordering wi...
Frédéric Koriche, Bruno Zanuttini
ICCV
2005
IEEE
14 years 8 months ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
NIPS
1998
13 years 8 months ago
Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
Shumeet Baluja
SIGCSE
2004
ACM
112views Education» more  SIGCSE 2004»
14 years 10 days ago
Using software testing to move students from trial-and-error to reflection-in-action
Introductory computer science students rely on a trial and error approach to fixing errors and debugging for too long. Moving to a reflection in action strategy can help students ...
Stephen H. Edwards
ICPR
2002
IEEE
14 years 8 months ago
Tracking People
This paper describes a real-time computer vision system for tracking people in monocular video sequences. The system tracks people as they move through the camera's field of ...
Ng Kim Piau, Surendra Ranganath