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Efficient Pruning of Probabilistic Automata [chapter]

Franck Thollard, Baptiste Jeudy
2008 Lecture Notes in Computer Science  
We propose in this article a method for pruning automata (when restricted to tree based structures) which is not only efficient (sub-quadratic) but that allows to dramatically reduce the size of the automaton  ...  Applications of probabilistic grammatical inference are limited due to time and space consuming constraints.  ...  Probabilistic Automata Definition 1.  ... 
doi:10.1007/978-3-540-89689-0_11 fatcat:oxfavoabwzedle2yqrzx5zy4ai

Position Models and Language Modeling [chapter]

Arnaud Zdziobeck, Franck Thollard
2008 Lecture Notes in Computer Science  
An alternative to this model is the probabilistic automaton.  ...  We propose here to improve the use of this model by restricting the dependency to a more reasonable value.  ...  We address in this section the building of probabilistic automata.  ... 
doi:10.1007/978-3-540-89689-0_12 fatcat:perwz65gsrbmflpk6hsnyi7o6i

Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms

P. Dupont, F. Denis, Y. Esposito
2005 Pattern Recognition  
It is proved that probabilistic deterministic automata (PDFA) form a proper subclass of probabilistic non-deterministic automata (PNFA). Two families of equivalent models are described next.  ...  Semi-probabilistic automata Definition 4.  ...  Probabilistic languages, automata and HMMs Probabilistic languages are defined in Section 2.1. We discuss in Section 2.2 various equivalent definitions of semi-probabilistic automata.  ... 
doi:10.1016/j.patcog.2004.03.020 fatcat:uytkvkyfpfbj3lhibry6cfwue4

Tiburon: A Weighted Tree Automata Toolkit [chapter]

Jonathan May, Kevin Knight
2006 Lecture Notes in Computer Science  
The availability of weighted finite-state string automata toolkits made possible great advances in natural language processing.  ...  To combat this problem, we introduce a weighted finite-state tree automata toolkit, which incorporates recent developments in weighted tree automata theory and is useful for natural language applications  ...  One way of avoiding long running times is to prune weighted automata before operating on them.  ... 
doi:10.1007/11812128_11 fatcat:pfdxcnllmfdepotrv2hn2bmar4

Distilling weighted finite automata from arbitrary probabilistic models

Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol
2019 Proceedings of the 14th International Conference on Finite-State Methods and Natural Language Processing  
Weighted finite automata (WFA) are often used to represent probabilistic models, such as n-gram language models, since they are efficient for recognition tasks in time and space.  ...  The proposed algorithm involves a counting step and a difference of convex optimization, both of which can be performed efficiently.  ...  The quantity γ(q s , q a ) can be computed as γ(q s , q a ) = π∈P * S∩A ((is,ia),(qs,qa)) w[π] where S ∩ A is the weighted intersection of automata S and A formed using an efficient ϕ-WFA intersection  ... 
doi:10.18653/v1/w19-3112 dblp:conf/fsmnlp/SureshR0S19 fatcat:tsrbwthjkfdptc7daiecyfau4a

Approximate Reduction of Finite Automata for High-Speed Network Intrusion Detection (Technical Report) [article]

Milan Ceska and Vojtech Havlena and Lukas Holik and Ondrej Lengal and Tomas Vojnar
2018 arXiv   pre-print
We consider the problem of approximate reduction of non-deterministic automata that appear in hardware-accelerated network intrusion detection systems (NIDSes).  ...  We define an error distance of a reduced automaton from the original one as the probability of packets being incorrectly classified by the reduced automaton (wrt the probabilistic distribution of packets  ...  We discuss the complexity of computing the probabilistic distance. Finally, we formulate two problems of approximate automata reduction via probabilistic distance.  ... 
arXiv:1710.08647v3 fatcat:4aqakfcq25a3naojaupb4d74b4

Designing and Evaluating an Interpretable Predictive Modeling Technique for Business Processes [chapter]

Dominic Breuker, Patrick Delfmann, Martin Matzner, Jörg Becker
2015 Lecture Notes in Business Information Processing  
To this end, we study the field of grammatical inference and identify suitable probabilistic modeling techniques for event log data.  ...  After tailoring one of these techniques to the domain of business process management, we derive a learning algorithm.  ...  This model can now serve as the probabilistic equivalent of automata as applied in the BPM domain.  ... 
doi:10.1007/978-3-319-15895-2_46 fatcat:cjjpbquaxfcn7huisczb7uideq

Random Generation of Deterministic Acyclic Automata Using the Recursive Method [chapter]

Sven De Felice, Cyril Nicaud
2013 Lecture Notes in Computer Science  
We also propose a lazy version of the algorithm that takes advantage of the typical shape of random acyclic automata to reduce experimentally the preprocessing.  ...  Using this algorithm, we provide some statistics on acyclic automata with up to 1000 states.  ...  Acknowledgements: we would like to thanks Arnaud Carayol for the very fruitful discussions we had during the preparation of this article.  ... 
doi:10.1007/978-3-642-38536-0_8 fatcat:dvb3nozyurfjpjny2yfs3ce7jy

Approximate Reduction of Finite Automata for High-Speed Network Intrusion Detection [chapter]

Milan Češka, Vojtěch Havlena, Lukáš Holík, Ondřej Lengál, Tomáš Vojnar
2018 Lecture Notes in Computer Science  
To formalise the intuitive notion of precision, we propose a novel probabilistic distance of automata.  ...  Our results provide experimental evidence that the method can be highly efficient in practice, allowing NIDSes to follow the rapid growth in the speed of networks. language-preserving automata reduction  ...  We discuss the complexity of computing the probabilistic distance. Finally, we formulate two problems of approximate automata reduction via probabilistic distance.  ... 
doi:10.1007/978-3-319-89963-3_9 fatcat:syyj7hxlgvhfpe2d4uscmeb6ti

A combined stochastic and greedy hybrid estimation capability for concurrent hybrid models with autonomous mode transitions

Lars Blackmore, Stanislav Funiak, Brian C. Williams
2008 Robotics and Autonomous Systems  
Probabilistic hybrid discrete/continuous models, such as Concurrent Probabilistic Hybrid Automata (CPHA) are convenient tools for modeling complex robotic systems.  ...  To accomplish this, we 1) develop an efficient stochastic sampling approach for CPHA based on Rao-Blackwellised Particle Filtering, 2) perform an empirical comparison of the greedy and stochastic approaches  ...  Concurrent Probabilistic Hybrid Automata We have previously developed Concurrent Probabilistic Hybrid Automata (CPHA) [8] , a formalism for modeling engineered systems that consist of a large number of  ... 
doi:10.1016/j.robot.2007.07.003 fatcat:ot7ydlz3x5hlfflr3ddpsootfe

Constraint-based analysis of concurrent probabilistic hybrid systems: An application to networked automation systems

Tino Teige, Andreas Eggers, Martin Fränzle
2011 Nonlinear Analysis. Hybrid Systems  
After formally introducing the computational model, we provide a mechanized translation scheme to encode probabilistic bounded reachability problems of concurrent probabilistic hybrid automata as linearly  ...  We explain in detail the formal model in terms of concurrent probabilistic automata, its encoding into the SiSAT modeling language, and finally the automated quantitative analysis.  ...  enhance readability of the article.  ... 
doi:10.1016/j.nahs.2010.04.009 fatcat:qicd6hvbjbhmrakz64kgg3faiy

Multiresolution Abnormal Trace Detection Using Varied-Length $n$-Grams and Automata

Guofei Jiang, Haifeng Chen, Cristian Ungureanu, Kenji Yoshihira
2007 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
Our key contribution is the novel use of varied-length n-grams and automata to characterize normal traces. A new trace is compared against the learned automata to determine whether it is abnormal.  ...  We inspect the trace constraints of real application software and verify the existence of long n-grams.  ...  N-gram extraction Theoretically, we can count the frequency of each trace and construct probabilistic automata to characterize the distribution of traces.  ... 
doi:10.1109/tsmcc.2006.871569 fatcat:77eajc327zhhxhgt3qyhpklag4

Approximating probabilistic models as weighted finite automata [article]

Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol
2021 arXiv   pre-print
Weighted finite automata (WFA) are often used to represent probabilistic models, such as n-gram language models, since they are efficient for recognition tasks in time and space.  ...  The proposed algorithm involves a counting step and a difference of convex optimization step, both of which can be performed efficiently.  ...  Algorithms to efficiently compute the intersection and shortest distance on WFAs are available in OpenFst [6] , an open-source weighted finite automata library.  ... 
arXiv:1905.08701v3 fatcat:txa6skom2reszpajdpjoffkg5q

Language Equivalence for Probabilistic Automata [chapter]

Stefan Kiefer, Andrzej S. Murawski, Joël Ouaknine, Björn Wachter, James Worrell
2011 Lecture Notes in Computer Science  
In this paper, we propose a new randomised algorithm for deciding language equivalence for probabilistic automata.  ...  deterministic ones in a majority of our test cases.  ...  representations of the languages of probabilistic automata [17] .  ... 
doi:10.1007/978-3-642-22110-1_42 fatcat:bkdzjaimevalhg5pripdollcs4

Page 5319 of Mathematical Reviews Vol. , Issue 82m [page]

1982 Mathematical Reviews  
Frumkin (Zb1 424: 10016) Pearl, Judea 82m:68071 The solution for the branching factor of the alpha-beta pruning algorithm.  ...  The author finds it impossible in general to favour one of the methods over the other and suggests a special combination of them as potentially the most efficient tool.  ... 
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