Learning discrete decomposable graphical models via constraint optimization
نویسندگان
چکیده
منابع مشابه
Learning discrete decomposable graphical models via constraint optimization
Statistical model learning problems are traditionally solved using either heuristic greedy optimization or stochastic simulation, such as Markov chain Monte Carlo or simulated annealing. Recently, there has been an increasing interest in the use of combinatorial search methods, including those based on computational logic. Some of these methods are particularly attractive since they can also be...
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ژورنال
عنوان ژورنال: Statistics and Computing
سال: 2015
ISSN: 0960-3174,1573-1375
DOI: 10.1007/s11222-015-9611-4