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ICCV
2005
IEEE
16 years 28 days ago
Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Zhuowen Tu
107
Voted
JMLR
2010
149views more  JMLR 2010»
14 years 5 months ago
Fast Committee-Based Structure Learning
Current methods for causal structure learning tend to be computationally intensive or intractable for large datasets. Some recent approaches have speeded up the process by first m...
Ernest Mwebaze, John A. Quinn
METMBS
2004
151views Mathematics» more  METMBS 2004»
15 years 12 days ago
Machine Learning Techniques for the Evaluation of External Skeletal Fixation Structures
In this thesis we compare several machine learning techniques for evaluating external skeletal fixation proposals. We experimented in the context of dog bone fractures but the pot...
Ning Suo, Khaled Rasheed, Walter D. Potter, Dennis...
ICCAD
1999
IEEE
95views Hardware» more  ICCAD 1999»
15 years 3 months ago
Dynamic power management using adaptive learning tree
Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic systems by selectively shutting down idle components. The quality of the shutdown control a...
Eui-Young Chung, Luca Benini, Giovanni De Micheli
HEURISTICS
2008
92views more  HEURISTICS 2008»
14 years 11 months ago
Learning heuristics for basic block instruction scheduling
Instruction scheduling is an important step for improving the performance of object code produced by a compiler. A fundamental problem that arises in instruction scheduling is to ...
Abid M. Malik, Tyrel Russell, Michael Chase, Peter...