A-posteriori Characterizations in Inductive Inference of Recursive Functions. - Thomas Zeugmann (J. Inf. Process. Cybern., 1983)

On the Synthesis of Fastest Programs in Inductive Inference. - Thomas Zeugmann (J. Inf. Process. Cybern., 1983)

Zur algorithmischen Synthese von schnellen Programmen. - Thomas Zeugmann (1983)

On the Nonboundability of total Effective Operators. - Thomas Zeugmann (Math. Log. Q., 1984)

On recursive optimizers. - Thomas Zeugmann (Mathematical Methods of Specification and Synthesis of Software Systems, 1985)

Inductive Inference of Almost Everywhere Correct Programs by Reliably Working Strategies. - Efim B. Kinber; Thomas Zeugmann (J. Inf. Process. Cybern., 1985)

On Barzdin's Conjecture. - Thomas Zeugmann (AII, 1986)

On the Power of Recursive Optimizers. - Thomas Zeugmann (Theor. Comput. Sci., 1988)

Refined Query Inference (Extended Abstract). - Efim B. Kinber; Thomas Zeugmann (AII, 1989)

Monte-Carlo Inference and Its Relations to Reliable Frequency Identification. - Efim B. Kinber; Thomas Zeugmann (FCT, 1989)

Improved Parallel Computations in the Ring Z/palpha. - Thomas Zeugmann (J. Inf. Process. Cybern., 1989)

Learning Via Queries With Teams and Anomilies. - Efim B. Kinber; William I. Gasarch; Thomas Zeugmann; Mark G. Pleszkoch; Carl H. Smith (COLT, 1990)

Computing Large Polynomial Powers Very Fast in Parallel. - Thomas Zeugmann (MFCS, 1990)

Inductive Inference of Optimal Programs: A Survey and Open Problems. - Thomas Zeugmann (Nonmonotonic and Inductive Logic, 1990)

Monotonic Versus Nonmonotonic Language Learning. - Steffen Lange; Thomas Zeugmann (Nonmonotonic and Inductive Logic, 1991)

One-Sided Error Probabilistic Inductive Inference and Reliable Frequency Identification - Efim B. Kinber; Thomas Zeugmann (Inf. Comput., 1991)

A Unifying Approach to Monotonic Language Learning on Informant. - Steffen Lange; Thomas Zeugmann (AII, 1992)

Too Much Can be Too Much for Learning Efficiently. - Rolf Wiehagen; Thomas Zeugmann (AII, 1992)

Types of Monotonic Language Learning and Their Characterization. - Steffen Lange; Thomas Zeugmann (COLT, 1992)

Highly Parallel Computations Modulo a Number Having Only Small Prime Factors - Thomas Zeugmann (Inf. Comput., 1992)

Language Learning in Dependence on the Space of Hypotheses. - Steffen Lange; Thomas Zeugmann (COLT, 1993)

Classification of predicates and languages. - Rolf Wiehagen; Carl H. Smith; Thomas Zeugmann (EuroCOLT, 1993)

Language Learning with a Bounded Number of Mind Changes. - Steffen Lange; Thomas Zeugmann (STACS, 1993)

Learning Recursive Languages with Bounded Mind Changes. - Steffen Lange; Thomas Zeugmann (Int. J. Found. Comput. Sci., 1993)

Average Case Analysis of Pattern Language Learning Algorithms (Abstract). - Thomas Zeugmann (AII/ALT, 1994)

Characterization of language learning front informant under various monotonicity constraints. - Steffen Lange; Thomas Zeugmann (J. Exp. Theor. Artif. Intell., 1994)

Ignoring data may be the only way to learn efficiently. - Rolf Wiehagen; Thomas Zeugmann (J. Exp. Theor. Artif. Intell., 1994)

Report on COLT 1994. - Thomas Zeugmann (SIGACT News, 1994)

Editor's Introduction. - Klaus P. Jantke; Takeshi Shinohara; Thomas Zeugmann (ALT, 1995)

Trading monotonicity demands versus mind changes. - Steffen Lange; Thomas Zeugmann (EuroCOLT, 1995)

Classifying Recursive Predicates and Languages. - Rolf Wiehagen; Carl H. Smith; Thomas Zeugmann (GOSLER Final Report, 1995)

Learning and Consistency. - Rolf Wiehagen; Thomas Zeugmann (GOSLER Final Report, 1995)

A Guided Tour Across the Boundaries of Learning Recursive Languages. - Thomas Zeugmann; Steffen Lange (GOSLER Final Report, 1995)

Learning via Queries with Teams and Anomalies. - William I. Gasarch; Efim B. Kinber; Mark G. Pleszkoch; Carl H. Smith; Thomas Zeugmann (Fundam. Informaticae, 1995)

Characterizations of Monotonic and Dual Monotonic Language Learning - Thomas Zeugmann; Steffen Lange; Shyam Kapur (Inf. Comput., 1995)

Learning by Erasing. - Steffen Lange; Rolf Wiehagen; Thomas Zeugmann (ALT, 1996)

Co-Learning of Recursive Languages from Positive Data. - Rusins Freivalds; Thomas Zeugmann (Ershov Memorial Conference, 1996)

Incremental Learning from Positive Data. - Steffen Lange; Thomas Zeugmann (J. Comput. Syst. Sci., 1996)

Set-Driven and Rearrangement-Independent Learning of Recursive Languages. - Steffen Lange; Thomas Zeugmann (Math. Syst. Theory, 1996)

Monotonic and Dual Monotonic Language Learning. - Steffen Lange; Thomas Zeugmann; Shyam Kapur (Theor. Comput. Sci., 1996)

Classifying Predicates and Languages. - Carl H. Smith; Rolf Wiehagen; Thomas Zeugmann (Int. J. Found. Comput. Sci., 1997)

Editor's Introduction. - Michael M. Richter; Carl H. Smith; Rolf Wiehagen; Thomas Zeugmann (ALT, 1998)

Learning One-Variable Pattern Languages in Linear Average Time. - Rüdiger Reischuk; Thomas Zeugmann (COLT, 1998)

Learning k-Variable Pattern Languages Efficiently Stochastically Finite on Average from Positive Data. - Peter Rossmanith; Thomas Zeugmann (ICGI, 1998)

Lange and Wiehagen's Pattern Language Learning Algorithm: An Average-Case Analysis with Respect to its Total Learning Time. - Thomas Zeugmann (Ann. Math. Artif. Intell., 1998)

On the Uniform Learnability of Approximations to Non-Recursive Functions. - Frank Stephan 001; Thomas Zeugmann (ALT, 1999)

A Complete and Tight Average-Case Analysis of Learning Monomials. - Rüdiger Reischuk; Thomas Zeugmann (STACS, 1999)

Incremental Concept Learning for Bounded Data Mining. - John Case; Sanjay Jain 001; Steffen Lange; Thomas Zeugmann (Inf. Comput., 1999)

Learning Recursive Concepts with Anomalies. - Gunter Grieser; Steffen Lange; Thomas Zeugmann (ALT, 2000)

Average-Case Complexity of Learning Polynomials. - Frank Stephan 001; Thomas Zeugmann (COLT, 2000)

An Average-Case Optimal One-Variable Pattern Language Learner. - Rüdiger Reischuk; Thomas Zeugmann (J. Comput. Syst. Sci., 2000)

Learning languages and functions by erasing. - Sanjay Jain 001; Efim B. Kinber; Steffen Lange; Rolf Wiehagen; Thomas Zeugmann (Theor. Comput. Sci., 2000)

Editors' Introduction. - Naoki Abe; Roni Khardon; Thomas Zeugmann (ALT, 2001)

Learning Recursive Functions Refutably. - Sanjay Jain 001; Efim B. Kinber; Rolf Wiehagen; Thomas Zeugmann (ALT, 2001)

Stochastic Finite Learning. - Thomas Zeugmann (SAGA, 2001)

Stochastic Finite Learning of the Pattern Languages. - Peter Rossmanith; Thomas Zeugmann (Mach. Learn., 2001)

Learning one-variable pattern languages very efficiently on average, in parallel, and by asking queries. - Thomas Erlebach; Peter Rossmanith; Hans Stadtherr; Angelika Steger; Thomas Zeugmann (Theor. Comput. Sci., 2001)

Foreword. - Rolf Wiehagen; Thomas Zeugmann (Theor. Comput. Sci., 2001)

Learning classes of approximations to non-recursive function. - Frank Stephan 001; Thomas Zeugmann (Theor. Comput. Sci., 2002)

Can Learning in the Limit Be Done Efficiently? - Thomas Zeugmann (ALT, 2003)

On learning of functions refutably. - Sanjay Jain 001; Efim B. Kinber; Rolf Wiehagen; Thomas Zeugmann (Theor. Comput. Sci., 2003)

A Polynomial Time Learner for a Subclass of Regular Patterns - John Case; Sanjay Jain 001; Rüdiger Reischuk; Frank Stephan 001; Thomas Zeugmann (Electron. Colloquium Comput. Complex., 2004)

Teaching Learners with Restricted Mind Changes. - Frank J. Balbach; Thomas Zeugmann (ALT, 2005)

Text Mining Using Markov Chains of Variable Length. - Björn Hoffmeister; Thomas Zeugmann (Federation over the Web, 2005)

Inductive inference of approximations for recursive concepts. - Steffen Lange; Gunter Grieser; Thomas Zeugmann (Theor. Comput. Sci., 2005)

Teaching Memoryless Randomized Learners Without Feedback. - Frank J. Balbach; Thomas Zeugmann (ALT, 2006)

Teaching Randomized Learners. - Frank J. Balbach; Thomas Zeugmann (COLT, 2006)

On the Teachability of Randomized Learners. - Frank J. Balbach; Thomas Zeugmann (Complexity of Boolean Functions, 2006)

Clustering Pairwise Distances with Missing Data: Maximum Cuts Versus Normalized Cuts. - Jan Poland; Thomas Zeugmann (Discovery Science, 2006)

Consistency Conditions for Inductive Inference of Recursive Functions. - Yohji Akama; Thomas Zeugmann (JSAI, 2006)

N-Gram Analysis Based on Zero-Suppressed BDDs. - Ryutaro Kurai; Shin-ichi Minato; Thomas Zeugmann (JSAI, 2006)

Inductive Inference and Language Learning. - Thomas Zeugmann (TAMC, 2006)

Learning a subclass of regular patterns in polynomial time. - John Case; Sanjay Jain 001; Rüdiger Reischuk; Frank Stephan 001; Thomas Zeugmann (Theor. Comput. Sci., 2006)

Foreword. - Nicolò Cesa-Bianchi; Rüdiger Reischuk; Thomas Zeugmann (Theor. Comput. Sci., 2006)

From learning in the limit to stochastic finite learning. - Thomas Zeugmann (Theor. Comput. Sci., 2006)

Foreword. - Shai Ben-David; John Case; Thomas Zeugmann (Theor. Comput. Sci., 2007)

Indistinguishability and First-Order Logic. - Skip Jordan; Thomas Zeugmann (TAMC, 2008)

Consistent and coherent learning with delta-delay. - Yohji Akama; Thomas Zeugmann (Inf. Comput., 2008)

Foreword. - John Case; Takeshi Shinohara; Thomas Zeugmann; Sandra Zilles (Theor. Comput. Sci., 2008)

Learning indexed families of recursive languages from positive data: A survey. - Steffen Lange; Thomas Zeugmann; Sandra Zilles (Theor. Comput. Sci., 2008)

Learning recursive functions: A survey. - Thomas Zeugmann; Sandra Zilles (Theor. Comput. Sci., 2008)

Recent Developments in Algorithmic Teaching. - Frank J. Balbach; Thomas Zeugmann (LATA, 2009)

Relational Properties Expressible with One Universal Quantifier Are Testable. - Charles Jordan; Thomas Zeugmann (SAGA, 2009)

Editors' Introduction. - Marcus Hutter; Frank Stephan 001; Vladimir Vovk; Thomas Zeugmann (ALT, 2010)

Clustering the Normalized Compression Distance for Influenza Virus Data. - Kimihito Ito; Thomas Zeugmann; Yu Zhu (Algorithms and Applications, 2010)

Recent Experiences in Parameter-Free Data Mining. - Kimihito Ito; Thomas Zeugmann; Yu Zhu (ISCIS, 2010)

Untestable Properties Expressible with Four First-Order Quantifiers. - Charles Jordan; Thomas Zeugmann (LATA, 2010)

A Note on the Testability of Ramsey's Class. - Charles Jordan; Thomas Zeugmann (TAMC, 2010)

Guest editors' foreword. - László Györfi; György Turán; Thomas Zeugmann (Theor. Comput. Sci., 2010)

Epsilon Covers. - Thomas Zeugmann (Encyclopedia of Machine Learning, 2010)

Epsilon Nets. - Thomas Zeugmann (Encyclopedia of Machine Learning, 2010)

PAC Learning. - Thomas Zeugmann (Encyclopedia of Machine Learning, 2010)

Stochastic Finite Learning. - Thomas Zeugmann (Encyclopedia of Machine Learning, 2010)

VC Dimension. - Thomas Zeugmann (Encyclopedia of Machine Learning, 2010)

Editors' Introduction. - Jyrki Kivinen; Csaba Szepesvári; Esko Ukkonen; Thomas Zeugmann (ALT, 2011)

On the Parameterised Complexity of Learning Patterns. - Frank Stephan 001; Ryo Yoshinaka; Thomas Zeugmann (ISCIS, 2011)

On the Amount of Nonconstructivity in Learning Recursive Functions. - Rusins Freivalds; Thomas Zeugmann (TAMC, 2011)

Untestable Properties in the Kahr-Moore-Wang Class. - Charles Jordan; Thomas Zeugmann (WoLLIC, 2011)

Teaching randomized learners with feedback. - Frank J. Balbach; Thomas Zeugmann (Inf. Comput., 2011)

Editors' Introduction. - Nader H. Bshouty; Gilles Stoltz; Nicolas Vayatis; Thomas Zeugmann (ALT, 2012)

On the Amount of Nonconstructivity in Learning Formal Languages from Positive Data. - Sanjay Jain 001; Frank Stephan 001; Thomas Zeugmann (TAMC, 2012)

Testable and untestable classes of first-order formulae. - Charles Jordan; Thomas Zeugmann (J. Comput. Syst. Sci., 2012)

Editors' Introduction. - Sanjay Jain 001; Rémi Munos; Frank Stephan 001; Thomas Zeugmann (ALT, 2013)

On the Size Complexity of Deterministic Frequency Automata. - Rusins Freivalds; Thomas Zeugmann; Grant R. Pogosyan (LATA, 2013)

Guest Editors' foreword. - Marcus Hutter; Frank Stephan 001; Vladimir Vovk; Thomas Zeugmann (Theor. Comput. Sci., 2013)

Editors' Introduction. - Peter Auer; Alexander Clark; Thomas Zeugmann; Sandra Zilles (ALT, 2014)

Active Learning of Recursive Functions by Ultrametric Algorithms. - Rusins Freivalds; Thomas Zeugmann (SOFSEM, 2014)

On the Influence of Technology on Learning Processes. - Ilja Kucevalovs; Ojars Krasts; Rusins Freivalds; Thomas Zeugmann (Parallel Process. Lett., 2014)

Guest Editors' foreword. - Nader H. Bshouty; Gilles Stoltz; Nicolas Vayatis; Thomas Zeugmann (Theor. Comput. Sci., 2014)

Guest Editors' introduction. - Jyrki Kivinen; Csaba Szepesvári; Thomas Zeugmann (Theor. Comput. Sci., 2014)

Image Analysis in a Parameter-Free Setting. - Yu Zhu; Thomas Zeugmann (ISCIS, 2015)

Mathematical Analysis and the Mathematics of Computation - Werner Römisch; Thomas Zeugmann (Springer, 2016)

The Kahr-Moore-Wang Class Contains Untestable Properties. - Charles Jordan; Thomas Zeugmann (Balt. J. Mod. Comput., 2016)

Obituary Rūsiņš Mārtiņš Freivalds (1942-2016). - Thomas Zeugmann (Bull. EATCS, 2016)

Guest editors' foreword. - Peter Auer; Alexander Clark; Thomas Zeugmann (Theor. Comput. Sci., 2016)

Guest Editors' foreword. - Sanjay Jain 001; Rémi Munos; Frank Stephan 001; Thomas Zeugmann (Theor. Comput. Sci., 2016)

Epsilon Cover. - Thomas Zeugmann (Encyclopedia of Machine Learning and Data Mining, 2017)

Epsilon Nets. - Thomas Zeugmann (Encyclopedia of Machine Learning and Data Mining, 2017)

PAC Learning. - Thomas Zeugmann (Encyclopedia of Machine Learning and Data Mining, 2017)

Stochastic Finite Learning. - Thomas Zeugmann (Encyclopedia of Machine Learning and Data Mining, 2017)

VC Dimension. - Thomas Zeugmann (Encyclopedia of Machine Learning and Data Mining, 2017)

On the Help of Bounded Shot Verifiers, Comparators and Standardisers for Learnability in Inductive Inference. - Ziyuan Gao; Sanjay Jain 001; Frank Stephan 001; Thomas Zeugmann (ALT, 2018)

Guest Editor's Foreword. - Thomas Zeugmann (Theor. Comput. Sci., 2018)

On the Interplay Between Inductive Inference of Recursive Functions, Complexity Theory and Recursive Numberings. - Thomas Zeugmann (CiE, 2020)

On the amount of nonconstructivity in learning formal languages from text. - Sanjay Jain 001; Frank Stephan 001; Thomas Zeugmann (Inf. Comput., 2021)