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» Selection of Subsets of Ordered Features in Machine Learning
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MICCAI
2005
Springer
16 years 14 days ago
Exploiting Temporal Information in Functional Magnetic Resonance Imaging Brain Data
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...
KDD
2009
ACM
215views Data Mining» more  KDD 2009»
16 years 4 days ago
Large-scale sparse logistic regression
Logistic Regression is a well-known classification method that has been used widely in many applications of data mining, machine learning, computer vision, and bioinformatics. Spa...
Jun Liu, Jianhui Chen, Jieping Ye
KDD
2005
ACM
125views Data Mining» more  KDD 2005»
15 years 5 months ago
Price prediction and insurance for online auctions
Online auctions are generating a new class of fine-grained data about online transactions. This data lends itself to a variety of applications and services that can be provided to...
Rayid Ghani
CEC
2009
IEEE
15 years 6 months ago
What is situated evolution?
—In this paper we discuss the notion of situated evolution. Our treatment includes positioning situated evolution on the map of evolutionary processes in terms of time- and space...
Martijn C. Schut, Evert Haasdijk, A. E. Eiben
COLT
2005
Springer
15 years 5 months ago
General Polynomial Time Decomposition Algorithms
We present a general decomposition algorithm that is uniformly applicable to every (suitably normalized) instance of Convex Quadratic Optimization and efficiently approaches an o...
Nikolas List, Hans-Ulrich Simon