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NIPS
1998
13 years 11 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
CVPR
2007
IEEE
15 years 6 days ago
Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition
Outdoor face recognition is among the most challenging problems for face recognition. In this paper, we develop a discriminant mutual subspace learning algorithm for indoor and ou...
Zhifeng Li, Dahua Lin, Helen M. Meng, Xiaoou Tang
MHCI
2005
Springer
14 years 3 months ago
Field-based mLearning: who wants what?
The real needs of end users of software technology are often neglected until it is too late. An approach is outlined that puts people before technology, and investigates the real ...
Paul Ryan, Enda Finn
AI
2001
Springer
14 years 2 months ago
Learning Bayesian Belief Network Classifiers: Algorithms and System
Abstract. This paper investigates the methods for learning predictive classifiers based on Bayesian belief networks (BN) – primarily unrestricted Bayesian networks and Bayesian m...
Jie Cheng, Russell Greiner
DIS
2008
Springer
13 years 12 months ago
Active Learning for High Throughput Screening
Abstract. An important task in many scientific and engineering disciplines is to set up experiments with the goal of finding the best instances (substances, compositions, designs) ...
Kurt De Grave, Jan Ramon, Luc De Raedt