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» Constraint Programming for Data Mining and Machine Learning
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SIGADA
2005
Springer
15 years 7 months ago
Experiences using SPARK in an undergraduate CS course
This paper describes experiences garnered while teaching a course on high integrity software using SPARK to a mix of junior and senior level undergraduates. The paper describes th...
Anthony S. Ruocco
CVPR
2010
IEEE
15 years 4 months ago
Co-clustering of Image Segments Using Convex Optimization Applied to EM Neuronal Reconstruction
This paper addresses the problem of jointly clustering two segmentations of closely correlated images. We focus in particular on the application of reconstructing neuronal structu...
Shiv Vitaladevuni, Ronen Basri
JMLR
2006
156views more  JMLR 2006»
15 years 1 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ICDE
2008
IEEE
137views Database» more  ICDE 2008»
16 years 3 months ago
Stop Chasing Trends: Discovering High Order Models in Evolving Data
Abstract-- Many applications are driven by evolving data -patterns in web traffic, program execution traces, network event logs, etc., are often non-stationary. Building prediction...
Shixi Chen, Haixun Wang, Shuigeng Zhou, Philip S. ...
ICML
2007
IEEE
16 years 2 months ago
Maximum margin clustering made practical
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
Kai Zhang, Ivor W. Tsang, James T. Kwok