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NIPS
2008
15 years 7 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
FLAIRS
2004
15 years 7 months ago
The Optimality of Naive Bayes
Naive Bayes is one of the most efficient and effective inductive learning algorithms for machine learning and data mining. Its competitive performance in classification is surpris...
Harry Zhang
IJWBC
2010
126views more  IJWBC 2010»
15 years 4 months ago
Self-supportive virtual communities
Learning Communities in healthcare is one approach in supporting practitioners and nurses to improve skills and knowledge and consequently support patients more efficiently. Web b...
Iraklis Varlamis, Ioannis Apostolakis
ECCV
2006
Springer
16 years 8 months ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
ASIACRYPT
2008
Springer
15 years 8 months ago
Universally Composable Adaptive Oblivious Transfer
In an oblivious transfer (OT) protocol, a Sender with messages M1, . . . , MN and a Receiver with indices 1, . . . , k [1, N] interact in such a way that at the end the Receiver ...
Matthew Green, Susan Hohenberger