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ICIP
2010
IEEE
13 years 5 months ago
Building Emerging Pattern (EP) Random forest for recognition
The Random forest classifier comes to be the working horse for visual recognition community. It predicts the class label of an input data by aggregating the votes of multiple tree...
Liang Wang, Yizhou Wang, Debin Zhao
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
13 years 11 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
ICCAD
2009
IEEE
159views Hardware» more  ICCAD 2009»
13 years 5 months ago
First steps towards SAT-based formal analog verification
Boolean satisfiability (SAT) based methods have traditionally been popular for formally verifying properties for digital circuits. We present a novel methodology for formulating a...
Saurabh K. Tiwary, Anubhav Gupta, Joel R. Phillips...
SIGMOD
2009
ACM
171views Database» more  SIGMOD 2009»
14 years 7 months ago
GAMPS: compressing multi sensor data by grouping and amplitude scaling
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Sorabh Gandhi, Suman Nath, Subhash Suri, Jie Liu
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales