Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
In this paper we show that many kernel methods can be adapted to deal with indefinite kernels, that is, kernels which are not positive semidefinite. They do not satisfy Mercer...
E cient learning of DFA is a challenging research problem in grammatical inference. Both exact and approximate (in the PAC sense) identi ability of DFA from examples is known to b...
In this paper we present an advanced functional extraction tool for automatic generation of high-level RTL from switch-level circuit netlist representation. The tool is called FEV...
Higher-order recursion schemes are systems of rewrite rules on typed non-terminal symbols, which can be used to define infinite trees. The Global Modal Mu-Calculus Model Checking...