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SETN
2004
Springer
16 years 1 days ago
Incremental Mixture Learning for Clustering Discrete Data
Abstract. This paper elaborates on an efficient approach for clustering discrete data by incrementally building multinomial mixture models through likelihood maximization using the...
Konstantinos Blekas, Aristidis Likas
ACL
2008
15 years 8 months ago
Searching Questions by Identifying Question Topic and Question Focus
This paper is concerned with the problem of question search. In question search, given a question as query, we are to return questions semantically equivalent or close to the quer...
Huizhong Duan, Yunbo Cao, Chin-Yew Lin, Yong Yu
NIPS
1998
15 years 8 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
CVPR
2003
IEEE
16 years 8 months ago
A Hybrid Approach for Computing Visual Hulls of Complex Objects
This paper addresses the problem of computing visual hulls from image contours. We propose a new hybrid approach which overcomes the precision-complexity trade-off inherent to vox...
Edmond Boyer, Jean-Sébastien Franco
KDD
2003
ACM
217views Data Mining» more  KDD 2003»
16 years 7 months ago
Algorithms for estimating relative importance in networks
Large and complex graphs representing relationships among sets of entities are an increasingly common focus of interest in data analysis--examples include social networks, Web gra...
Scott White, Padhraic Smyth