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» Learning of Boolean Functions Using Support Vector Machines
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GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
14 years 2 months ago
Extraction of informative genes from microarray data
Identification of those genes that might anticipate the clinical behavior of different types of cancers is challenging due to availability of a smaller number of patient samples...
Topon Kumar Paul, Hitoshi Iba
DAC
2005
ACM
13 years 11 months ago
A combined feasibility and performance macromodel for analog circuits
The need to reuse the performance macromodels of an analog circuit topology challenges existing regression based modeling techniques. A model of good reusability should have a num...
Mengmeng Ding, Ranga Vemuri
KDD
2008
ACM
104views Data Mining» more  KDD 2008»
14 years 9 months ago
Learning methods for lung tumor markerless gating in image-guided radiotherapy
In an idealized gated radiotherapy treatment, radiation is delivered only when the tumor is at the right position. For gated lung cancer radiotherapy, it is difficult to generate ...
Ying Cui, Jennifer G. Dy, Gregory C. Sharp, Brian ...
WEA
2005
Springer
119views Algorithms» more  WEA 2005»
14 years 2 months ago
On Symbolic Scheduling Independent Tasks with Restricted Execution Times
Ordered Binary Decision Diagrams (OBDDs) are a data structure for Boolean functions which supports many useful operations. It finds applications in CAD, model checking, and symbol...
Daniel Sawitzki
JCP
2008
104views more  JCP 2008»
13 years 9 months ago
Analysis and Improved Recognition of Protein Names Using Transductive SVM
We first analyzed protein names using various dictionaries and databases and found five problems with protein names; i.e., the treatment of special characters, the treatment of hom...
Masaki Murata, Tomohiro Mitsumori, Kouichi Doi