The LSV seminar takes place on Tuesday at 11:00 AM. The usual location is the conference room at Pavillon des Jardins (venue). If you wish to be informed by e-mail about upcoming seminars, please contact Stéphane Le Roux and Matthias Fuegger.

The seminar is open to public and does not require any form of registration.

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- Date
- Tuesday, January 22 2019 at 11:00AM
- Place
- Pavillon des Jardins
- Speaker
- Susanna Donatelli (University of Torino, Italy and invited Prof. at LSV)

In this talk I will review the stochastic logic CSL TA, a logic that has been defined to model-check Continuous Time Markov Chains. CSL TA extends the well-known stochastic logic CSL by allowing path properties to be defined through a Timed Automaton (TA). The price of this extension is an increase in the cost of the model checking algorithm both in terms of memory and of solution time: the model checking of CSL requires to solve one of more CTMCs, that of CSL TA the solution of a Markov Regenerative Process. I will then discuss how we can efficiently model check CSL TA properties, in particular I will present a model-checking algorithm that adapts itself to the formula, so that the memory and computational cost for the model checking of a CSL TA formula naturally scales down to that of the standard CSL model checking algorithm, when the property specified by the TA is equivalent to a CSL one. The technique is based on the construction of the region graph of the timed automata and on a component-based technique for the computation of the steady-state probability of Markov regenerative processes. The presentation will be supported by a demo with the GreatSPN tool developed in Torino.

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- Date
- Tuesday, January 29 2019 at 11:00AM
- Place
- Pavillon des Jardins
- Speaker
- Ohad Kammar (University of Edinburgh)

I will describe our recent work on statistical probabilistic programming languages. These are expressive languages for describing generative Bayesian models of the kinds used in computational statistics and machine learning. We give an adequate denotational semantics for a calculus with recursive higher-order types, continuous probability distributions, and soft constraints. Among them are untyped languages, similar to Church and WebPPL, because our semantics allows recursive mixed-variance datatypes. Our semantics justifies important program equivalences including commutativity. Our new semantic model is based on `quasi-Borel predomains'. These are a mixture of chain-complete partial orders (cpos) and quasi-Borel spaces. Quasi-Borel spaces are a recent model of probability theory that focuses on sets of admissible random elements. I will give a brief introduction to quasi-Borel spaces and predomains, and their properties. Probability is traditionally treated in cpo models using probabilistic powerdomains, but these are not known to be commutative on any class of cpos with higher-order functions. By contrast, quasi-Borel predomains do support both a commutative probabilistic powerdomain and higher-order functions, which I will describe. For more details on this joint work with Matthijs Vákár and Sam Staton, see: Matthijs Vákár, Ohad Kammar, and Sam Staton. 2019. A Domain Theory for Statistical Probabilistic Programming. Proc. ACM Program. Lang. 3, POPL, Article 36 (January 2019), 35 pages., DOI: 10.1145/3290349.

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- Date
- Tuesday, February 05 2019 at 11:00AM
- Place
- Pavillon des Jardins
- Speaker
- Pablo Arrighi (Aix-Marseille University)

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- Date
- Tuesday, February 19 2019 at 11:00AM
- Place
- Pavillon des Jardins
- Speaker
- Olivier Bournez (LIX)

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Export agenda in iCalendar format | Past seminars

- Tue, Jan 22
- Tue, Jan 29
- Tue, Feb 5
- Tue, Feb 19