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» On Latent Belief Structures
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ICCV
2011
IEEE
12 years 10 months ago
Latent Low-Rank Representation for Subspace Segmentation and Feature Extraction
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
Guangcan Liu, Shuicheng Yan
ECSQARU
2001
Springer
14 years 2 months ago
The Search of Causal Orderings: A Short Cut for Learning Belief Networks
Abstract. Although we can build a belief network starting from any ordering of its variables, its structure depends heavily on the ordering being selected: the topology of the netw...
Silvia Acid, Luis M. de Campos, Juan F. Huete
AAAI
1990
13 years 11 months ago
Symbolic Probabilistic Inference in Belief Networks
The Symbolic Probabilistic Inference (SPI) Algorithm [D'Ambrosio, 19891 provides an efficient framework for resolving general queries on a belief network. It applies the conc...
Ross D. Shachter, Bruce D'Ambrosio, Brendan Del Fa...
INFOCOM
2003
IEEE
14 years 3 months ago
Associative Search in Peer to Peer Networks: Harnessing Latent Semantics
— The success of a P2P file-sharing network highly depends on the scalability and versatility of its search mechanism. Two particularly desirable search features are scope (abil...
Edith Cohen, Amos Fiat, Haim Kaplan
NLE
2011
13 years 23 days ago
Modeling reciprocity in social interactions with probabilistic latent space models
Reciprocity is a pervasive concept that plays an important role in governing people’s behavior, judgments, and thus their social interactions. In this paper we present an analys...
Roxana Girju, Michael J. Paul