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» Algorithmic randomness of continuous functions
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117
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AAAI
2011
14 years 2 months ago
Fast Newton-CG Method for Batch Learning of Conditional Random Fields
We propose a fast batch learning method for linearchain Conditional Random Fields (CRFs) based on Newton-CG methods. Newton-CG methods are a variant of Newton method for high-dime...
Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Ok...
116
Voted
ICPR
2006
IEEE
16 years 3 months ago
A 'No Panacea Theorem' for Multiple Classifier Combination
We introduce the `No Panacea Theorem' for classifier combination in the two-classifier, two-class case. It states that if the combination function is continuous and diverse, ...
Robert I. Damper, Roland Hu
139
Voted
DASFAA
2007
IEEE
202views Database» more  DASFAA 2007»
15 years 9 months ago
Optimizing Moving Queries over Moving Object Data Streams
With the increasing in demand on location-based aware services and RFIDs, efficient processing of continuous queries over moving object streams becomes important. In this paper, w...
Dan Lin, Bin Cui, Dongqing Yang
VLSID
2005
IEEE
120views VLSI» more  VLSID 2005»
15 years 8 months ago
On Finding Consecutive Test Vectors in a Random Sequence for Energy-Aware BIST Design
During pseudorandom testing, a significant amount of energy and test application time is wasted for generating and for applying “useless” test vectors that do not contribute t...
Sheng Zhang, Sharad C. Seth, Bhargab B. Bhattachar...
144
Voted
CVPR
2008
IEEE
16 years 4 months ago
Interactive image segmentation via minimization of quadratic energies on directed graphs
We propose a scheme to introduce directionality in the Random Walker algorithm for image segmentation. In particular, we extend the optimization framework of this algorithm to com...
Dheeraj Singaraju, Leo Grady, René Vidal