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» Random Constraint Satisfaction: A More Accurate Picture
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CVPR
2007
IEEE
15 years 11 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic
ICCAD
2002
IEEE
143views Hardware» more  ICCAD 2002»
15 years 6 months ago
A Markov chain sequence generator for power macromodeling
In macromodeling-based power estimation, circuit macromodels are created from simulations of synthetic input vector sequences. Fast generation of these sequences with all possible...
Xun Liu, Marios C. Papaefthymiou
STOC
2009
ACM
167views Algorithms» more  STOC 2009»
15 years 10 months ago
Universally utility-maximizing privacy mechanisms
A mechanism for releasing information about a statistical database with sensitive data must resolve a trade-off between utility and privacy. Publishing fully accurate information ...
Arpita Ghosh, Tim Roughgarden, Mukund Sundararajan
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 10 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
KDD
2010
ACM
259views Data Mining» more  KDD 2010»
15 years 1 months ago
A probabilistic model for personalized tag prediction
Social tagging systems have become increasingly popular for sharing and organizing web resources. Tag recommendation is a common feature of social tagging systems. Social tagging ...
Dawei Yin, Zhenzhen Xue, Liangjie Hong, Brian D. D...