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Learning Probabilistic Residual Finite State Automata
[chapter]

2002
*
Lecture Notes in Computer Science
*

We introduce a new class of

doi:10.1007/3-540-45790-9_7
fatcat:go6ap7enwjhnflnwve4ayalj74
*probabilistic**automata*:*Probabilistic**Residual**Finite**State**Automata*. ... We prove that there are more languages generated by PRFA than by*Probabilistic*Deterministic*Finite**Automata*(PDFA). ...*Probabilistic**residual**finite**state**automata*(PRFA) We introduce in this section the class of*probabilistic**residual**finite**state**automata*(PRFA). ...##
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Residuality and Learning for Nondeterministic Nominal Automata
[article]

2022
*
arXiv
*
pre-print

This property enables active

arXiv:1910.11666v7
fatcat:w2qd6tv4o5hypbhu62urhlluwu
*learning*algorithms, and makes up for the fact that*residuality*-- a semantic property -- is undecidable for nominal*automata*. ... To answer it, we develop the theory of*residual*nominal*automata*, a subclass of nondeterministic nominal*automata*. ... We thank Borja Balle for references on*residual**probabilistic*languages, and Henning Urbat for discussions on nominal lattice theory. ...##
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Residuality and Learning for Nondeterministic Nominal Automata

2022
*
Logical methods in computer science : LMCS 18(1)
*

This property enables active

doi:10.18154/rwth-2022-01916
fatcat:lyzgpncm7jcr5ijewbmsmknpey
*learning*algorithms, and makes up for the fact that*residuality*-a semantic property -is undecidable for nominal*automata*. ... To answer it, we develop the theory of*residual*nominal*automata*, a subclass of nondeterministic nominal*automata*. ... We thank Borja Balle for references on*residual**probabilistic*languages, and Henning Urbat for discussions on nominal lattice theory. ...##
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PAutomaC: a probabilistic automata and hidden Markov models learning competition

2013
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Machine Learning
*

The

doi:10.1007/s10994-013-5409-9
fatcat:ey3ghvxqxzbevmpzxmv5tytvay
*Probabilistic**Automata**learning*Competition (PAutomaC), run in 2012, was the first grammatical inference challenge that allowed the comparison between these methods and algorithms. ... grammars and*finite**state*machines and the relevant literature. ...*residual**finite**state**automata*(Prfa) [31] , and multiplicity*automata*(Ma) [9, 8] (or weighted*automata*[54] ). ...##
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Active Automata Learning in Practice
[chapter]

2018
*
Lecture Notes in Computer Science
*

Five years ago (in 2011) we have surveyed the then current

doi:10.1007/978-3-319-96562-8_5
fatcat:jtpzftrzvzf3tdtbncntfc4s4q
*state*of active*automata**learning*research and applications of active*automata**learning*in practice. ... Active*automata**learning*is slowly becoming a standard tool in the toolbox of the software engineer. ...*finite**state**automata*. ...##
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Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms

2005
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Pattern Recognition
*

On the other hand, HMMs with final probabilities and

doi:10.1016/j.patcog.2004.03.020
fatcat:uytkvkyfpfbj3lhibry6cfwue4
*probabilistic**automata*generate distributions over strings of*finite*length. ... A semi-*probabilistic*automaton 2 (semi-PA) is a 5-tuple , Q, , , where is a*finite*alphabet, Q is a*finite*set of*states*, : Q × × Q → [0, 1] is a mapping defining the transition probability function, : ... Esposito et al. study the identification of*probabilistic**residual**finite**state**automata*(PRFA). The PRFA class includes properly the PDFA class and is strictly included in the PNFA class [45] . ...##
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Some Classes of Regular Languages Identifiable in the Limit from Positive Data
[chapter]

2002
*
Lecture Notes in Computer Science
*

*Probabilistic*

*Residual*

*Finite*

*State*

*Automata*p. 77 Fragmentation: Enhancing Identifiability p. 92 On Limit Points for Some Variants of Rigid Lambek Grammars p. 106 Generalized Stochastic Tree ...

*Automata*for Multi-relational Data Mining p. 120 On Sufficient Conditions to Identify Classes of Grammars from Polynomial Time and Data p. 134 Stochastic Grammatical Inference with Multinomial Tests ...

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Learning Classes of Probabilistic Automata
[chapter]

2004
*
Lecture Notes in Computer Science
*

*Probabilistic*

*finite*

*automata*(PFA) model stochastic languages, i.e. probability distributions over strings. Inferring PFA from stochastic data is an open field of research. ... Finally, we propose a

*learning*algorithm for a subclass of PFA, called PRFA. ...

*Probabilistic*

*Residual*

*Finite*

*Automata*Definition 2 (

*Probabilistic*

*Residual*

*Finite*Automaton). ...

##
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Rational stochastic languages
[article]

2006
*
arXiv
*
pre-print

We define the notion of

arXiv:cs/0602093v1
fatcat:4gz4cyxfqber3f5puh5gpljwx4
*residual*of a stochastic language and we use it to investigate properties of several subclasses of rational stochastic languages. ... Lastly, we study the representation of rational stochastic languages by means of multiplicity*automata*. ...*Residual**Automata*(PRA), i.e.*probabilistic**automata*whose structure is a*residual**finite**state*automaton (RFSA) [CO94, CO99, dlHT00, ELDD02, DE04] . ...##
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How to measure the topological quality of protein grammars?
[article]

2017
*
arXiv
*
pre-print

Context-free and context-sensitive formal grammars are often regarded as more appropriate to model proteins than regular level models such as

arXiv:1611.10078v2
fatcat:eunzyetdwnaqdndmzn5ufnw7ke
*finite**state**automata*and Hidden Markov Models. ... In theory, the claim is well founded in the fact that many biologically relevant interactions between*residues*of protein sequences have a character of nested or crossed dependencies. ... Context-free (CF) and context-sensitive (CS) formal grammars are often regarded as more appropriate to model proteins than regular level models such as*finite**state**automata*and Hidden Markov Models (HMM ...##
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Using Pseudo-Stochastic Rational Languages in Probabilistic Grammatical Inference
[article]

2008
*
arXiv
*
pre-print

The estimate of P stands in some class of

arXiv:cs/0607085v2
fatcat:2x3xe6svgfdevg67o2m6mwf4pi
*probabilistic*models such as*probabilistic**automata*(PA). In this paper, we focus on*probabilistic*models based on multiplicity*automata*(MA). ... In*probabilistic*grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. ... A new*state*will be added to the automaton if the*residual*language corresponding to (ux) −1 p s cannot be approximated as a linear combination of the*residual*languages corresponding the*states*already ...##
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Learning Probability Distributions Generated by Finite-State Machines
[chapter]

2016
*
Topics in Grammatical Inference
*

The methods we review are

doi:10.1007/978-3-662-48395-4_5
fatcat:u4cepbpghjcv7ct6zoqrgir2cy
*state*merging and*state*splitting methods for*probabilistic*deterministic*automata*and the recently developed spectral method for nondeterministic*probabilistic**automata*. ... to account for the error introduced by a*finite*sample. ...*Probabilistic**Automata*A*probabilistic**finite*automaton (pfa) of size n is a tuple Q, Σ , τ, α 0 , α ∞ where Q is a set of n*states*, Σ is a*finite*alphabet, τ : Q × Σ × Q → [0, 1] is the transition probability ...##
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Compositional Stochastic Model Checking Probabilistic Automata via Assume-guarantee Reasoning

2020
*
International Journal of Networked and Distributed Computing (IJNDC)
*

is a popular active

doi:10.2991/ijndc.k.190918.001
fatcat:55ee6cvpp5btfdox3qg7qezyci
*learning*algorithm (since they can ask queries actively) for*Residual**Finite*-*State**Automata*(RFSA) [35, 36] . ... Generally, the RFSA may generate extra nondeterministic choices in the product PA [37] and it is a subclass of Nondeterministic*Finite*-*state**Automata*(NFA). ...##
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Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference
[chapter]

2006
*
Lecture Notes in Computer Science
*

The estimate of P stands in some class of

doi:10.1007/11872436_10
fatcat:zhpwf32bpngahkxkwcqblwg6qq
*probabilistic*models such as*probabilistic**automata*(PA). In this paper, we focus on*probabilistic*models based on multiplicity*automata*(MA). ... In*probabilistic*grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. ... A new*state*will be added to the automaton if the*residual*language corresponding to (ux) −1 p s cannot be approximated as a linear combination of the*residual*languages corresponding the*states*already ...##
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Automated Learning of Probabilistic Assumptions for Compositional Reasoning
[chapter]

2011
*
Lecture Notes in Computer Science
*

We do so using algorithmic

doi:10.1007/978-3-642-19811-3_2
fatcat:ghpdevjwxndgrhjo35deeqxgeq
*learning*techniques, which have already proved to be successful for the generation of assumptions for compositional verification of non-*probabilistic*systems. ... We discuss recent developments in the area of automated compositional verification techniques for*probabilistic*systems. ... Whereas L**learns*a minimal DFA for a regular language, the algorithm NL* [7]*learns*a minimal*residual**finite*-*state*automaton (RFSA). RFSAs are a subclass of nondeterministic*finite**automata*. ...
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