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AAAI
2006
15 years 6 months ago
Model Counting: A New Strategy for Obtaining Good Bounds
Model counting is the classical problem of computing the number of solutions of a given propositional formula. It vastly generalizes the NP-complete problem of propositional satis...
Carla P. Gomes, Ashish Sabharwal, Bart Selman
TCSV
2008
148views more  TCSV 2008»
15 years 4 months ago
Modeling Background and Segmenting Moving Objects from Compressed Video
Abstract--Modeling background and segmenting moving objects are significant techniques for video surveillance and other video processing applications. Most existing methods of mode...
Weiqiang Wang, Jie Yang, Wen Gao
JMLR
2011
111views more  JMLR 2011»
14 years 11 months ago
Models of Cooperative Teaching and Learning
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
ECCV
2002
Springer
16 years 6 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal
ICML
2005
IEEE
16 years 5 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...