There are two main topics in this paper: (i) Vietnamese words are recognized and sentences are segmented into words by using probabilistic models; (ii) the optimum probabilistic mo...
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Here we advocate an approach to learning hardware based on induction of finite state machines from temporal logic constraints. The method involves training on examples, constraint...
Marek A. Perkowski, Alan Mishchenko, Anatoli N. Ch...
The last few years have seen the advent of a new breed of decision procedures for various fragments of first-order logic based on ional abstraction. A lazy satisfiability checker ...
—Logical initializability is the property of a gate-level circuit whereby it can be driven to a unique start state when simulated by a three-valued (0, 1, ) simulator. In practic...