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SETN
2004
Springer
15 years 11 months 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
HM
2007
Springer
155views Optimization» more  HM 2007»
15 years 10 months ago
A Hybrid ILS Heuristic to the Referee Assignment Problem with an Embedded MIP Strategy
Optimization in sports is a field of increasing interest. A novel problem in sports management is the Referee Assignment Problem, in which a limited number of referees with differe...
Alexandre R. Duarte, Celso C. Ribeiro, Sebasti&aac...
CVPR
2008
IEEE
15 years 7 months ago
A rank constrained continuous formulation of multi-frame multi-target tracking problem
This paper presents a multi-frame data association algorithm for tracking multiple targets in video sequences. Multi-frame data association involves finding the most probable corr...
Khurram Shafique, Mun Wai Lee, Niels Haering
NIPS
2007
15 years 7 months ago
Convex Clustering with Exemplar-Based Models
Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
Danial Lashkari, Polina Golland
SBACPAD
2004
IEEE
83views Hardware» more  SBACPAD 2004»
15 years 7 months ago
Parallel Adaptive Mesh Coarsening for Seismic Tomography
Seismic tomography enables to model the internal structure of the Earth. In order to improve the precision of existing models, a huge amount of acquired seismic data must be analy...
Marc Grunberg, Stéphane Genaud, Catherine M...