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194
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NIPS
2008
15 years 8 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
VLDB
1998
ACM
312views Database» more  VLDB 1998»
15 years 10 months ago
WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
Gholamhosein Sheikholeslami, Surojit Chatterjee, A...
194
Voted
WISE
2002
Springer
15 years 11 months ago
A Unified Framework for Clustering Heterogeneous Web Objects
In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a un...
Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma
IJCV
2008
106views more  IJCV 2008»
15 years 6 months ago
A Model-Selection Framework for Multibody Structure-and-Motion of Image Sequences
Given an image sequence of a scene consisting of multiple rigidly moving objects, multi-body structure-and-motion (MSaM) is the task to segment the image feature tracks into the d...
Konrad Schindler, David Suter, Hanzi Wang
ICCV
2007
IEEE
16 years 8 months ago
Vector Quantizing Feature Space with a Regular Lattice
Most recent class-level object recognition systems work with visual words, i.e., vector quantized local descriptors. In this paper we examine the feasibility of a dataindependent ...
Tinne Tuytelaars, Cordelia Schmid