35 citations · 70 across the 9 of their papers we have counts for
13 papers
Introducing Divergence for Infinite Probabilistic Models
Alain Finkel, Serge Haddad, Lina Ye
Computing the reachability probability in infinite state probabilistic models has been the topic of numerous works. Here we introduce a new property called \emph{divergence} that w…
Analyzing Robustness of Angluin's L Algorithm in Presence of Noise
Lina Ye, Igor Khmelnitsky, Serge Haddad +5
Angluin's L algorithm learns the minimal deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approximatively…
About Decisiveness of Dynamic Probabilistic Models
Alain Finkel, Serge Haddad, Lina Ye
Decisiveness of infinite Markov chains with respect to some (finite or infinite) target set of states is a key property that allows to compute the reachability probability of this…
Analyzing Robustness of Angluin's L* Algorithm in Presence of Noise
Igor Khmelnitsky, Serge Haddad, Lina Ye +5
Angluin's L* algorithm learns the minimal (complete) deterministic finite automaton (DFA) of a regular language using membership and equivalence queries. Its probabilistic approxim…
Coverability, Termination, and Finiteness in Recursive Petri Nets
Alain Finkel, Serge Haddad, Igor Khmelnitsky
In the early two-thousands, Recursive Petri nets have been introduced in order to model distributed planning of multi-agent systems for which counters and recursivity were necessar…
Property-Directed Verification of Recurrent Neural Networks
Igor Khmelnitsky, Daniel Neider, Rajarshi Roy +6
This paper presents a property-directed approach to verifying recurrent neural networks (RNNs). To this end, we learn a deterministic finite automaton as a surrogate model from a g…