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JMLR Workshop and Conference Proceedings

Volume 57: Proceedings of The 13th International Conference on Grammatical Inference

Editors: Sicco Verwer, Menno van Zaanen, Rick Smetsers

Contents:

Accepted Papers

International Conference on Grammatical Inference 2016: Preface

Sicco Verwer, Menno van Zaanen, Rick Smetsers

Simple K-star Categorial Dependency Grammars and their Inference

Denis Béchet, Annie Foret

Query Learning Automata with Helpful Labels

Adrian-Horia Dediu, Joana M. Matos, Claudio Moraga

Inferring Non-resettable Mealy Machines with n States

Roland Groz, Catherine Oriat, Nicolas Brémond

Testing Distributional Properties of Context-Free Grammars

Alexander Clark

Learning Top-Down Tree Transducers with Regular Domain Inspection

Adrien Boiret, Aurélien Lemay, Joachim Niehren

Using Model Theory for Grammatical Inference: a Case Study from Phonology

Kristina Strother-Garcia, Jerey Heinz, Hyun Jin Hwangbo

The Generalized Smallest Grammar Problem

Payam Siyari, Matthias Gallé

Online Grammar Compression for Frequent Pattern Discovery

Shouhei Fukunaga, Yoshimasa Takabatake, Tomohiro I, Hiroshi Sakamoto

Sp2Learn: A Toolbox for the Spectral Learning of Weighted Automata

Denis Arrivault, Dominique, Benielli, François Denis, Remi Eyraud

Learning Deterministic Finite Automata from Infinite Alphabets

Gaetano Pellegrino, Christian Hammerschmidt, Qin Lin, Sicco Verwer

Results of the Sequence PredIction ChallengE (SPiCe): a Competition on Learning the Next Symbol in a Sequence

Borja Balle, Rémi Eyraud, Franco M. Luque, Ariadna Quattoni, Sicco Verwer

Predicting Sequential Data with LSTMs Augmented with Strictly 2-Piecewise Input Vectors

Chihiro Shibata, Jeffrey Heinz

A Spectral Method that Worked Well in the SPiCe’16 Competition

Farhana Ferdousi Liza, Marek Grześ

Evaluation of Machine Learning Methods on SPiCe

Ichinari Sato, Kaizaburo Chubachi, Diptarama

Flexible State-Merging for Learning (P)DFAs in Python

Christian Hammerschmidt, Benjamin Loos, Radu State, Thomas Engel

Model Selection of Sequence Prediction Algorithms by Compression

Du Xi, Dai Zhuang

Sequence Prediction Using Neural Network Classiers

Yanpeng Zhao, Shanbo Chu, Yang Zhou, Kewei Tu