Title :
Multi-thread search with deterministic annealing EM algorithm
Author :
Takada, Masaharu ; Nakano, Ryohei
Author_Institution :
Nagoya Inst. of Technol., Japan
fDate :
6/24/1905 12:00:00 AM
Abstract :
The EM algorithm is an efficient algorithm to obtain the ML estimate for incomplete data, but has the local optimality problem. The deterministic annealing expectation-maximization (DAEM) algorithm was once proposed to solve the problem, but is not guaranteed to obtain the global optimum since it employs a single token search. The paper investigates the possibility of the multiple-thread search with the DAEM algorithm for a Gaussian mixture. The experiments showed the minimal beam size to guarantee the global optimality is not so large for a Gaussian mixture, and the solution quality of the beam DAEM algorithm always exceeds the EM and DAEM algorithms
Keywords :
Gaussian distribution; multi-threading; search problems; simulated annealing; Gaussian mixture; ML estimate; deterministic annealing EM algorithm; efficient algorithm; global optimum; incomplete data; local optimality problem; minimal beam size; multithread search; Annealing; Bifurcation; Clustering algorithms; Computational efficiency; Cooling; Embedded computing; Iterative algorithms; Maximum likelihood estimation; Temperature;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005618
