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KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
UAI
2004
13 years 9 months ago
Recovering Articulated Object Models from 3D Range Data
We address the problem of unsupervised learning of complex articulated object models from 3D range data. We describe an algorithm whose input is a set of meshes corresponding to d...
Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang,...
JMLR
2008
169views more  JMLR 2008»
13 years 8 months ago
Multi-class Discriminant Kernel Learning via Convex Programming
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
Jieping Ye, Shuiwang Ji, Jianhui Chen
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
FOIKS
2006
Springer
14 years 3 days ago
Reasoning Support for Expressive Ontology Languages Using a Theorem Prover
It is claimed in [45] that first-order theorem provers are not efficient for reasoning with ontologies based on description logics compared to specialised description logic reasone...
Ian Horrocks, Andrei Voronkov