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» Evaluating algorithms that learn from data streams
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ICML
2009
IEEE
15 years 11 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
ICIP
2009
IEEE
16 years 5 months ago
Learning Large Margin Likelihoods For Realtime Head Pose Tracking
We consider the problem of head tracking and pose estimation in realtime from low resolution images. Tracking and pose recognition are treated as two coupled problems in a probabi...
PERCOM
2007
ACM
16 years 3 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
ICMLA
2007
15 years 5 months ago
Semi-Supervised Active Learning for Modeling Medical Concepts from Free Text
We apply a new active learning formulation to the problem of learning medical concepts from unstructured text. The new formulation is based on maximizing the mutual information th...
Rómer Rosales, Praveen Krishnamurthy, R. Bh...
ICASSP
2010
IEEE
15 years 4 months ago
A H.264/AVC video database for the evaluation of quality metrics
This paper describes a publicly available database of subjective scores, relative to quality assessment of 156 video streams encoded with H.264/AVC and corrupted by simulating pac...
Francesca De Simone, Marco Tagliasacchi, Matteo Na...