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A Categorical Framework for Learning Generalised Tree Automata [article]

Gerco van Heerdt, Tobias Kappé, Jurriaan Rot, Matteo Sammartino, Alexandra Silva
2020 arXiv   pre-print
We instantiate the abstract theory to a large class of Set functors, by which we recover for the first time practical tree automata learning algorithms from an abstract framework and at the same time obtain  ...  Automata learning is a popular technique used to automatically construct an automaton model from queries.  ...  framework for automata learning based on (co)algebra.  ... 
arXiv:2001.05786v1 fatcat:pevfelvmcjedfmcpj43na4kpva

Tree Automata as Algebras: Minimisation and Determinisation [article]

Gerco van Heerdt, Tobias Kappé, Jurriaan Rot, Matteo Sammartino, Alexandra Silva
2019 arXiv   pre-print
We study a categorical generalisation of tree automata, as Σ-algebras for a fixed endofunctor Σ endowed with initial and final states.  ...  We build upon and extend an existing generalisation of the Nerode equivalence to a categorical setting, and relate it to the existence of minimal automata.  ...  Tree automata, categorically In this section we start our categorical investigation of (bottom-up) tree automata.  ... 
arXiv:1904.08802v1 fatcat:viekhxtihfcn3jrujycshvroii

On the role of locality in learning stress patterns

Jeffrey Heinz
2009 Phonology  
A learning algorithm is presented which generalises by failing to distinguish same-neighbourhood environments perceived in the learner's linguistic input – hence learning neighbourhood-distinct patterns  ...  AbstractThis paper presents a previously unnoticed universal property of stress patterns in the world's languages: they are, for small neighbourhoods, neighbourhood-distinct.  ...  Figure 8 8 The learning framework.17 This result holds even in other learning frameworks with different criteria for success, e.g. the Probably Approximately Correct framework (Valiant 1984 ; see Anthony  ... 
doi:10.1017/s0952675709990145 fatcat:sy47wkbi3jftlm7uoqxk6kww2q

Minimisation in Logical Form [article]

Nick Bezhanishvili and Marcello Bonsangue and Helle Hvid Hansen and Dexter Kozen and Clemens Kupke and Prakash Panangaden and Alexandra Silva
2020 arXiv   pre-print
Stone-type dualities provide a powerful mathematical framework for studying properties of logical systems.  ...  In this paper we propose a general categorical framework within which such minimisation algorithms can be understood. The goal is to provide a unifying perspective based on duality.  ...  For weighted automata, we use our framework to extend a well-known result for weighted automata over a field [65] to weighted automata over a principal ideal domain: the minimal weighted automaton over  ... 
arXiv:2005.11551v1 fatcat:v72fxl3yj5dd5gr3qteo6rxvaa

A New Approach for Active Automata Learning Based on Apartness [article]

Frits Vaandrager, Bharat Garhewal, Jurriaan Rot, Thorsten Wißmann
2021 arXiv   pre-print
We present L^#, a new and simple approach to active automata learning.  ...  L^# does not require auxiliary notions such as observation tables or discrimination trees, but operates directly on tree-shaped automata.  ...  , 30] , Mealy machines with timers [65] , visibly pushdown automata [36] , and categorical generalisations of automata [63, 29, 12, 18] .  ... 
arXiv:2107.05419v3 fatcat:ynzfnlsatjd7lclen2ubbshvjm

Incremental Monoidal Grammars [article]

Dan Shiebler, Alexis Toumi, Mehrnoosh Sadrzadeh
2020 arXiv   pre-print
This allows us to link the categorical viewpoint on natural language to the standard machine learning notion of probabilistic language model.  ...  Generalising from the Booleans to arbitrary semirings, we extend our construction to weighted formal grammars and weighted automata.  ...  Coalgebras Coalgebras are a useful framework for categorically modeling dynamical systems.  ... 
arXiv:2001.02296v2 fatcat:6i2w3xlizractausumhfjjwkqi

On Learning Nominal Automata with Binders

Yi Xiao, Emilio Tuosto
2019 Electronic Proceedings in Theoretical Computer Science  
We investigate a learning algorithm in the context of nominal automata, an extension of classical automata to alphabets featuring names.  ...  We propose a learning algorithm on nominal regular languages with binders. Our algorithm generalises Angluin's L* algorithm with respect to nominal regular languages with binders.  ...  We designed a learning algorithm for a class of languages over infinite alphabet; more precisely, we have considered nominal regular languages with binders [25, 27] .  ... 
doi:10.4204/eptcs.304.9 fatcat:3g22jydynjdxda6yrdms2gd7ty

Fast Computations on Ordered Nominal Sets [article]

David Venhoek, Joshua Moerman, Jurriaan Rot
2020 arXiv   pre-print
We evaluate ONS in two applications: minimisation of automata and active automata learning.  ...  Our main motivation is nominal automata, which are models for recognising languages over infinite alphabets.  ...  For general comments and suggestions we would like to thank Ugo Montanari and Niels van der Weide.  ... 
arXiv:1902.08414v2 fatcat:htbgousrenh5pfdmlpcdhng2we

Predicting Sequences of Traversed Nodes in Graphs using Network Models with Multiple Higher Orders [article]

Christoph Gote, Giona Casiraghi, Frank Schweitzer, Ingo Scholtes
2021 arXiv   pre-print
We propose a novel sequence prediction method for sequential data capturing node traversals in graphs.  ...  Our method builds on a statistical modelling framework that combines multiple higher-order network models into a single multi-order model.  ...  Other methods use Petri nets [3, 45] , decision trees [13, 22, 29] , graph and network models [26, 32] , spectral learning [4] , as well as neural networks and automata [42] .  ... 
arXiv:2007.06662v2 fatcat:lemgsweojfcavfdk7eaxcmh73e

Foundations of Reversible Computation [chapter]

Bogdan Aman, Gabriel Ciobanu, Robert Glück, Robin Kaarsgaard, Jarkko Kari, Martin Kutrib, Ivan Lanese, Claudio Antares Mezzina, Łukasz Mikulski, Rajagopal Nagarajan, Iain Phillips, G. Michele Pinna (+3 others)
2020 Lecture Notes in Computer Science  
Quantum machine learning is the aspect of quantum computing concerned with the design of algorithms capable of generalised learning from labelled training data by effectively exploiting quantum effects  ...  While the present section aims to give an overview of the use of categorical models in providing categorical semantics for reversible programming languages, categorical models have also been studied for  ... 
doi:10.1007/978-3-030-47361-7_1 fatcat:3qgnwqrqnvdltkqjbuzfgx7wty

State of the art of network protocol reverse engineering tools

Julien Duchêne, Colas Le Guernic, Eric Alata, Vincent Nicomette, Mohamed Kaâniche
2017 Journal in Computer Virology and Hacking Techniques  
A description, at different levels of detail, is necessary for many applications, such as interoperability or security audits.  ...  Moreover, keeping pace with a protocol evolutions was a real challenge. Supporting interoperability is not the only motivation for using reverse engineering.  ...  These techniques consist in decomposing the learning of the automata into sub-automata related in the actions performed on the system.  ... 
doi:10.1007/s11416-016-0289-8 fatcat:bybg6liixbbodekvt2tvrllffi

Database Issues in Knowledge Discovery and Data Mining

Chris Rainsford, John Roddick
1999 Australasian Journal of Information Systems  
The terms "Knowledge Discovery in Databases" and "Data Mining" have been adopted for a field of research dealing with the automatic discovery of knowledge impb'cit within databases.  ...  Data mining is useful in situations where the volume of data is either too large or too complicated for manual processing or, to a lesser extent, where human experts are unavailable to provide knowledge  ...  However this is only possible if a framework for generalising temporal intervals is provided.  ... 
doi:10.3127/ajis.v6i2.310 fatcat:57zzkqzw2bdgndhjp5tumgicd4

On Computability, Learnability and Extractability of Finite State Machines from Recurrent Neural Networks [article]

Reda Marzouk
2020 arXiv   pre-print
As for learnability, an extension of the active learning framework better suited to the problem of approximating RNNs with FSMs is proposed, with the aim of better formalizing the problem of RNN approximation  ...  Theoretical analysis of two possible scenarions in this framework were performed.  ...  The learning framework is rich with many alternative learning scenarios.  ... 
arXiv:2009.06398v1 fatcat:qow5uzwcezd7vafuobfocs4dye

A Review on the Service Virtualisation and Its Structural Pillars

Zeinab Farahmandpour, Mehdi Seyedmahmoudian, Alex Stojcevski
2021 Applied Sciences  
This paper provides a review of the relevant research within these four fields by carrying out a structured study on about 80 research works.  ...  This paper reviews the state-of-the-art of how these areas have been used in automating the service virtualisation to make available the required environment for testing software.  ...  In the automata learning phase, it generates automata utilising the rules extracted to minimise inaccurate generalisations.  ... 
doi:10.3390/app11052381 fatcat:hqp47almpnet3kty7zikqmaqga

PhD Abstracts

GRAHAM HUTTON
2014 Journal of functional programming  
If a student or advisor would like to submit a dissertation abstract for publication in this series, please contact the editor for further details.  ...  The abstracts are freely available on the JFP website, i.e. not behind any paywall, and do not require any transfer for copyright, merely a license from the author.  ...  Tree homomorphisms are a very limited form of tree automata that transform the tree structure depending only on local information.  ... 
doi:10.1017/s0956796814000215 fatcat:rs2j5wgm5ndf7ek2zls5pmg2w4
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