The Special Issue on

Algorithmic Learning Theory

for ALT 2013 in

Theoretical Computer Science

ALT 13 Logo

appeared in

Theoretical Computer Science Volume 620, March 21, 2016.

The Special Issue on Algorithmic Learning Theory has been edited by Sanjay Jain, Rémi Munos, Frank Stephan, and Thomas Zeugmann.

Table of Contents

Sanjay Jain, Rémi Munos, Frank Stephan, and Thomas Zeugmann
Guest Editors' Foreword, Free download until April 9, 2016.

pp. 1–3

Jara Uitto and Roger Wattenhofer
On competitive recommendations ,

pp. 4–14

Ziyuan Gao, Frank Stephan, and Sandra Zilles,
Partial learning of recursively enumerable languages,
pp. 15–32

John Case and Timo Kötzing.
Topological separations in inductive inference,
pp. 33–45

Chihiro Shibata and Ryo Yoshinaka.
Probabilistic learnability of context-free grammars with basic distributional properties from positive examples,
pp. 46–72

Malte Darnstädt, Thorsten Kiss, Hans Ulrich Simon, and Sandra Zilles.
Order compression schemes,
pp. 73–90

Anna Choromanska, Krzysztof Choromanski, Geetha Jagannathan, and Claire Monteleoni.
Differentially-private learning of low dimensional manifolds,
pp. 91–104

Lee-Ad Gottlieb, Aryeh Kontorovich, and Robert Krauthgamer.
Adaptive metric dimensionality reduction,
pp. 105–118

Azadeh Khaleghi and Daniil Ryabko.
Nonparametric multiple change point estimation in highly dependent time series,
pp. 119–133

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