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» Hierarchical exploration of large multivariate data sets
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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
14 years 3 months ago
Sparse Kernel SVMs via Cutting-Plane Training
We explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. ...
Thorsten Joachims, Chun-Nam John Yu
ICRA
2005
IEEE
102views Robotics» more  ICRA 2005»
14 years 2 months ago
Planning 3-D Path Networks in Unstructured Environments
Abstract— In this paper, we explore the problem of threedimensional motion planning in highly cluttered and unstructured outdoor environments. Because accurate sensing and modeli...
Nicolas Vandapel, James Kuffner, Omead Amidi
WACV
2005
IEEE
14 years 2 months ago
Ensemble Methods in the Clustering of String Patterns
We address the problem of clustering of contour images from hardware tools based on string descriptions, in a comparative study of cluster combination techniques. Several clusteri...
André Lourenço, Ana L. N. Fred
ICTAI
2010
IEEE
13 years 6 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
IEEEVAST
2010
13 years 3 months ago
Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological opera
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each ob...
Bilkis J. Ferdosi, Hugo Buddelmeijer, Scott Trager...