Volume 57: International Conference on Grammatical Inference, 5-7 October 2016, Delft, The Netherlands

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Editors: Sicco Verwer, Menno van Zaanen, Rick Smetsers

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International Conference on Grammatical Inference 2016: Preface

Sicco Verwer, Menno van Zaanen, Rick Smetsers ; PMLR 57:1-2

Simple K-star Categorial Dependency Grammars and their Inference

Denis Béchet, Annie Foret ; PMLR 57:3-14

Query Learning Automata with Helpful Labels

Adrian-Horia Dediu, Joana M. Matos, Claudio Moraga ; PMLR 57:15-29

Inferring Non-resettable Mealy Machines with $n$ States

Roland Groz, Catherine Oriat, Nicolas Brémond ; PMLR 57:30-41

Testing Distributional Properties of Context-Free Grammars

Alexander Clark ; PMLR 57:42-53

Learning Top-Down Tree Transducers with Regular Domain Inspection

Adrien Boiret, Aurélien Lemay, Joachim Niehren ; PMLR 57:54-65

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

Kristina Strother-Garcia, Jerey Heinz, Hyun Jin Hwangbo ; PMLR 57:66-78

The Generalized Smallest Grammar Problem

Payam Siyari, Matthias Gallé ; PMLR 57:79-92

Online Grammar Compression for Frequent Pattern Discovery

Shouhei Fukunaga, Yoshimasa Takabatake, Tomohiro I, Hiroshi Sakamoto ; PMLR 57:93-104

Sp2Learn: A Toolbox for the Spectral Learning of Weighted Automata

Denis Arrivault, Dominique Benielli, François Denis, Remi Eyraud ; PMLR 57:105-119

Learning Deterministic Finite Automata from Infinite Alphabets

Gaetano Pellegrino, Christian Hammerschmidt, Qin Lin, Sicco Verwer ; PMLR 57:120-131

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 ; PMLR 57:132-136

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

Chihiro Shibata, Jeffrey Heinz ; PMLR 57:137-142

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

Farhana Ferdousi Liza, Marek Grześ ; PMLR 57:143-148

Evaluation of Machine Learning Methods on SPiCe

Ichinari Sato, Kaizaburo Chubachi, Diptarama ; PMLR 57:149-153

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

Christian Hammerschmidt, Benjamin Loos, Radu State, Thomas Engel ; PMLR 57:154-159

Model Selection of Sequence Prediction Algorithms by Compression

Du Xi, Dai Zhuang ; PMLR 57:160-163

Sequence Prediction Using Neural Network Classiers

Yanpeng Zhao, Shanbo Chu, Yang Zhou, Kewei Tu ; PMLR 57:164-169

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