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KDD
2008
ACM
150views Data Mining» more  KDD 2008»
14 years 8 months ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
CP
2007
Springer
13 years 11 months ago
Efficient Computation of Minimal Point Algebra Constraints by Metagraph Closure
Abstract. Computing the minimal network (or minimal CSP) representation of a given set of constraints over the Point Algebra (PA) is a fundamental reasoning problem. In this paper ...
Alfonso Gerevini, Alessandro Saetti
JMLR
2008
209views more  JMLR 2008»
13 years 7 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
MONET
2006
107views more  MONET 2006»
13 years 7 months ago
Utilization and fairness in spectrum assignment for opportunistic spectrum access
The Open Spectrum approach to spectrum access can achieve near-optimal utilization by allowing devices to sense and utilize available spectrum opportunistically. However, a naive d...
Chunyi Peng, Haitao Zheng, Ben Y. Zhao
SIROCCO
2010
13 years 9 months ago
Traffic Grooming in Star Networks via Matching Techniques
The problem of grooming is central in studies of optical networks. In graph-theoretic terms, it can be viewed as assigning colors to given paths in a graph, so that at most g (the ...
Ignasi Sau, Mordechai Shalom, Shmuel Zaks