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ICML
2008
IEEE
16 years 14 days ago
An RKHS for multi-view learning and manifold co-regularization
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...
Vikas Sindhwani, David S. Rosenberg
GECCO
2003
Springer
160views Optimization» more  GECCO 2003»
15 years 4 months ago
Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System
This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A comb...
Behrouz Minaei-Bidgoli, William F. Punch
TIP
2010
182views more  TIP 2010»
14 years 6 months ago
Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
ISCA
1998
IEEE
136views Hardware» more  ISCA 1998»
15 years 3 months ago
Exploiting Spatial Locality in Data Caches Using Spatial Footprints
Modern cache designs exploit spatial locality by fetching large blocks of data called cache lines on a cache miss. Subsequent references to words within the same cache line result...
Sanjeev Kumar, Christopher B. Wilkerson
ISBRA
2007
Springer
15 years 5 months ago
Noise-Based Feature Perturbation as a Selection Method for Microarray Data
Abstract. DNA microarrays can monitor the expression levels of thousands of genes simultaneously, providing the opportunity for the identification of genes that are differentiall...
Li Chen, Dmitry B. Goldgof, Lawrence O. Hall, Stev...