Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Discovering the dependencies among the variables of a domain from examples is an important problem in optimization. Many methods have been proposed for this purpose, but few large...
Existing optimization algorithms for the multiplierless realization of multiple constant multiplications (MCM) typically target the minimization of the number of addition and subt...
Levent Aksoy, Eduardo Costa, Paulo F. Flores, Jos&...
An attractive mechanism to specify global constraints in rostering and other domains is via formal languages. For instance, the REGULAR and GRAMMAR constraints specify constraints ...
— The last two decades have seen many efficient algorithms and architectures for the design of low-complexity bit-parallel Multiple Constant Multiplications (MCM) operation, tha...