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» Learning by Propagability
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MMM
2010
Springer
141views Multimedia» more  MMM 2010»
13 years 9 months ago
Slow Intelligence Systems
: Networks and distributed computing systems are becoming increasingly important and at the same time, more and more critical to the world of Information Technology. This rash spre...
Shi-Kuo Chang
NN
1998
Springer
13 years 7 months ago
Multilayer neural networks and Bayes decision theory
There are many applications of multilayer neural networks to pattern classification problems in the engineering field. Recently, it has been shown that Bayes a posteriori probab...
Ken-ichi Funahashi
SAT
2009
Springer
132views Hardware» more  SAT 2009»
14 years 2 months ago
Relaxed DPLL Search for MaxSAT
We propose a new incomplete algorithm for the Maximum Satisfiability (MaxSAT) problem on unweighted Boolean formulas, focused specifically on instances for which proving unsatis...
Lukas Kroc, Ashish Sabharwal, Bart Selman
CVPR
2008
IEEE
14 years 9 months ago
Active microscopic cellular image annotation by superposable graph transduction with imbalanced labels
Systematic content screening of cell phenotypes in microscopic images has been shown promising in gene function understanding and drug design. However, manual annotation of cells ...
Jun Wang, Shih-Fu Chang, Xiaobo Zhou, Stephen T. C...
AAAI
2006
13 years 9 months ago
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies
Reasoning with both probabilistic and deterministic dependencies is important for many real-world problems, and in particular for the emerging field of statistical relational lear...
Hoifung Poon, Pedro Domingos