We study complexity and approximation of queries in an expressive query language for probabilistic databases. The language studied supports the compositional use of confidence com...
We take a dual view of Markov processes ? advocated by Kozen ? as transformers of bounded measurable functions. We redevelop the theory of labelled Markov processes from this view ...
Philippe Chaput, Vincent Danos, Prakash Panangaden...
Background: Probabilistic models for sequence comparison (such as hidden Markov models and pair hidden Markov models for proteins and mRNAs, or their context-free grammar counterp...
In machine learning theory, problem classes are distinguished because of di erences in complexity. In 6 , a stochastic model of learning from examples was introduced. This PAClear...
In this paper, we propose a novel statistical capacitance extraction method for interconnects considering process variations. The new method, called statCap, is based on the spect...