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ICML
2004
IEEE
16 years 4 months ago
Multiple kernel learning, conic duality, and the SMO algorithm
While classical kernel-based classifiers are based on a single kernel, in practice it is often desirable to base classifiers on combinations of multiple kernels. Lanckriet et al. ...
Francis R. Bach, Gert R. G. Lanckriet, Michael I. ...
144
Voted
KDD
2007
ACM
210views Data Mining» more  KDD 2007»
15 years 9 months ago
Machine learning for stock selection
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
Robert J. Yan, Charles X. Ling
128
Voted
DATAMINE
2002
125views more  DATAMINE 2002»
15 years 3 months ago
High-Performance Commercial Data Mining: A Multistrategy Machine Learning Application
We present an application of inductive concept learning and interactive visualization techniques to a large-scale commercial data mining project. This paper focuses on design and c...
William H. Hsu, Michael Welge, Thomas Redman, Davi...
156
Voted
CVPR
2011
IEEE
14 years 11 months ago
Learning Message-Passing Inference Machines for Structured Prediction
Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Stephane Ross, Daniel Munoz, J. Andrew Bagnell
128
Voted
NN
2006
Springer
15 years 3 months ago
Machine learning in soil classification
In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the cons...
Biswanath Bhattacharya, Dimitri P. Solomatine