We describe a method for the fully automatic learning of hierarchical finite state translation models. The input to the method is transcribed speech utterances and their correspon...
We use a formal tool to extract Finite State Machines (FSM) based representations (lists of states and transitions) of sequential circuits described by flip-flops and gates. The...
Most hardware description frameworks, whether schematic or textual, use cooperating finite state machines (CFSM) as the underlying abstraction. In the CFSM framework, a designer ...
With the availability of chip multiprocessor (CMP) and simultaneous multithreading (SMT) machines, extracting thread level parallelism from a sequential program has become crucial...
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...