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» Finding low-utility data structures
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KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 9 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
WWW
2004
ACM
14 years 9 months ago
RDFPeers: a scalable distributed RDF repository based on a structured peer-to-peer network
Centralized Resource Description Framework (RDF) repositories have limitations both in their failure tolerance and in their scalability. Existing Peer-to-Peer (P2P) RDF repositori...
Min Cai, Martin R. Frank
CVPR
2004
IEEE
14 years 10 months ago
Inference of Multiple Subspaces from High-Dimensional Data and Application to Multibody Grouping
Multibody grouping is a representative of applying subspace constraints in computer vision tasks. Under linear projection models, feature points of multibody reside in multiple su...
Zhimin Fan, Jie Zhou, Ying Wu
CORR
2012
Springer
185views Education» more  CORR 2012»
12 years 4 months ago
Bayesian network learning with cutting planes
The problem of learning the structure of Bayesian networks from complete discrete data with a limit on parent set size is considered. Learning is cast explicitly as an optimisatio...
James Cussens
SODA
2004
ACM
107views Algorithms» more  SODA 2004»
13 years 10 months ago
A note on the nearest neighbor in growth-restricted metrics
In this paper, we give results relevant to sequential and distributed dynamic data structures for finding nearest neighbors in growth-restricted metrics. Our sequential data struc...
Kirsten Hildrum, John Kubiatowicz, Sean Ma, Satish...