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CVPR
2010
IEEE
16 years 19 days ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
IPPS
2009
IEEE
15 years 11 months ago
Toward adjoinable MPI
4 Automatic differentiation is the primary means of obtaining analytic5 derivatives from a numerical model given as a computer program. There-6 fore, it is an essential productivi...
Jean Utke, Laurent Hascoët, Patrick Heimbach,...
154
Voted
VLSID
2002
IEEE
151views VLSI» more  VLSID 2002»
16 years 5 months ago
Mode Selection and Mode-Dependency Modeling for Power-Aware Embedded Systems
Among the many techniques for system-level power management, it is not currently possible to guarantee timing constraints and have a comprehensive system model at the same time. S...
Dexin Li, Pai H. Chou, Nader Bagherzadeh
CORR
2011
Springer
174views Education» more  CORR 2011»
14 years 8 months ago
Parameter Learning of Logic Programs for Symbolic-Statistical Modeling
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a ...
Yoshitaka Kameya, Taisuke Sato
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
15 years 9 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen