Rolf Wiehagen

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Connections between Identifying Functionals, standardizing Operations, and Computable Numberings

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1984, Math. Log. Q..

Language Learning from Texts: Degrees of Intrinsic Complexity and Their Characterizations

Rolf Wiehagen, Sanjay Jain, Efim B. Kinber, 2000, J. Comput. Syst. Sci..

Probabilistic Versus Deterministic Inductive Inference in Nonstandard Numberings

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1988, Math. Log. Q..

Generalization versus classification

Carl H. Smith, Rolf Wiehagen, Rolf Wiehagen, 1992, COLT '92.

On the power of learning robustly

Carl H. Smith, Rolf Wiehagen, Sanjay Jain, 1998, COLT' 98.

Identifying nearly minimal Gödel numbers from additional information

Rusins Freivalds, Ognian Botuscharov, Rolf Wiehagen, 2004, Annals of Mathematics and Artificial Intelligence.

Learning from Good Examples

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1995, GOSLER Final Report.

Inductive Inference of Recursive Functions

Rolf Wiehagen, 1975, MFCS.

From Inductive Inference to Algorithmic Learning Theory

Rolf Wiehagen, 1992, ALT.

Identification of Formal Languages

Rolf Wiehagen, Rolf Wiehagen, 1977, MFCS.

Robust learning--rich and poor

John Case, Rolf Wiehagen, Sanjay Jain, 2004, J. Comput. Syst. Sci..

Dual Types of Hypotheses in Inductive Inference

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1991, Nonmonotonic and Inductive Logic.

When unlearning helps

John Case, Rolf Wiehagen, Frank Stephan, 2008, Inf. Comput..

From Inductive Inference to Algorithmic Learning Theory (Invented).

Rolf Wiehagen, 1994 .

Learning by Erasing

Rolf Wiehagen, Thomas Zeugmann, Steffen Lange, 1996, ALT.

On the intrinsic complexity of learning recursive functions

Carl H. Smith, Rolf Wiehagen, Efim B. Kinber, 1999, COLT '99.

On the intrinsic complexity of learning recursive functions

Carl H. Smith, Rolf Wiehagen, Sanjay Jain, 2003, Inf. Comput..

How fast is program synthesis from examples

Rolf Wiehagen, 1985, Mathematical Methods of Specification and Synthesis of Software Systems.

Classifying Predicates and Languages

Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann, 1997, Int. J. Found. Comput. Sci..

Editor's Introduction

Rolf Wiehagen, Thomas Zeugmann, Michael M. Richter, 1998, ALT.

Learning all subfunctions of a function

Rolf Wiehagen, Sanjay Jain, Efim B. Kinber, 2004, Inf. Comput..

On the Complexity of Effective Program Synthesis

Rolf Wiehagen, Rolf Wiehagen, 1986, AII.

Learning Recursive Functions Refutably

Rolf Wiehagen, Sanjay Jain, Thomas Zeugmann, 2001, ALT.

On the Complexity of Program Synthesis from Examples

Rolf Wiehagen, Rolf Wiehagen, 1986, J. Inf. Process. Cybern..

Rekursionstheoretische Charakterisierung von erkennbaren Klassen rekursiver Funktionen

Rolf Wiehagen, Hermann Jung, 1977, J. Inf. Process. Cybern..

Charakteristische Eigenschaften von erkennbaren Klassen rekursiver Funktionen

Rolf Wiehagen, Walter Liepe, Rolf Wiehagen, 1976, J. Inf. Process. Cybern..

Inductive Inference and Computable One-One Numberings

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1982, Math. Log. Q..

Robust Learning - Rich and Poor

John Case, Rolf Wiehagen, Sanjay Jain, 2001, COLT/EuroCOLT.

Learning and Consistency

Rolf Wiehagen, Thomas Zeugmann, Rolf Wiehagen, 1995, GOSLER Final Report.

On the Power of Probabilistic Inductive Inference in Nonstandard Numberings

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1989, J. Inf. Process. Cybern..

Characterization Problems in the Theory of Inductive Inference

Rolf Wiehagen, Rolf Wiehagen, 1978, ICALP.

Polynomial-Time Inference of Pattern Languages

Rolf Wiehagen, Steffen Lange, Rolf Wiehagen, 1990, ALT.

On Learning and Co-learning of Minimal Programs

Rolf Wiehagen, Sanjay Jain, Efim B. Kinber, 1996, ALT.

Classifying Recursive Predicates and Languages

Carl H. Smith, Rolf Wiehagen, Thomas Zeugmann, 1995, GOSLER Final Report.

On learning of functions refutably

Rolf Wiehagen, Sanjay Jain, Thomas Zeugmann, 2003, Theor. Comput. Sci..

Learning Small Programs with Additional Information

Carl H. Smith, Rusins Freivalds, Rolf Wiehagen, 1997, LFCS.

Learning languages and functions by erasing

Rolf Wiehagen, Sanjay Jain, Thomas Zeugmann, 2000, Theor. Comput. Sci..

Classification of predicates and languages

Rolf Wiehagen, Thomas Zeugmann, Carl Smith, 1994 .

Inductive Inference with Additional Information

Rolf Wiehagen, R. V. Freivald, 1979, J. Inf. Process. Cybern..

How Inductive Inference Strategies Discover Their Errors

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1995, Inf. Comput..

A Thesis in Inductive Inference

Rolf Wiehagen, 1990, Nonmonotonic and Inductive Logic.

On Learning Multiple Concepts in Parallel

Carl H. Smith, Rolf Wiehagen, Efim B. Kinber, 1995, J. Comput. Syst. Sci..

Inductive Inference from Good Examples

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1989, AII.

Learning All Subfunctions of a Function

Rolf Wiehagen, Sanjay Jain, Efim B. Kinber, 2003, COLT.

Ignoring data may be the only way to learn efficiently

Rolf Wiehagen, Thomas Zeugmann, Rolf Wiehagen, 1994, J. Exp. Theor. Artif. Intell..

Polynomial-time inference of arbitrary pattern languages

Rolf Wiehagen, Steffen Lange, 2009, New Generation Computing.

From inductive inference to algorithmic learning theory

Rolf Wiehagen, 2009, New Generation Computing.

On the Power of Inductive Inference from Good Examples

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1993, Theor. Comput. Sci..

Robust Learning Is Rich

Carl H. Smith, Rolf Wiehagen, Sanjay Jain, 2001, J. Comput. Syst. Sci..

Learning recursive languages from good examples

Rolf Wiehagen, Jochen Nessel, Steffen Lange, 2004, Annals of Mathematics and Artificial Intelligence.

Limes-Erkennung rekursiver Funktionen durch spezielle Strategien

Rolf Wiehagen, 1975, J. Inf. Process. Cybern..

Learning by the Process of Elimination

Carl H. Smith, Marek Karpinski, Rusins Freivalds, 2002, Inf. Comput..

On learning multiple concepts in parallel

Carl H. Smith, Rolf Wiehagen, Efim B. Kinber, 1993, COLT '93.

Error Detecting in Inductive Inference

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1995, GOSLER Final Report.

Dechiffrierung von ND-Automaten

Rolf Wiehagen, 1975, J. Inf. Process. Cybern..

On the Power of Probabilistic Strategies in Inductive Inference

Rusins Freivalds, Rolf Wiehagen, Efim B. Kinber, 1984, Theor. Comput. Sci..

Research in the theory of inductive inference by GDR mathematicians - A survey

Rolf Wiehagen, Reinhard Klette, Rolf Wiehagen, 1980, Inf. Sci..

Generalization versus classification

Carl H. Smith, Rolf Wiehagen, 1995, J. Exp. Theor. Artif. Intell..

Too Much Can be Too Much for Learning Efficiently

Rolf Wiehagen, Thomas Zeugmann, 1992, AII.

On the role of search for learning from examples

Stuart A. Kurtz, Carl H. Smith, Rolf Wiehagen, 2001, J. Exp. Theor. Artif. Intell..

Language Learning from Good Examples

Rolf Wiehagen, Jochen Nessel, Steffen Lange, 1994, AII/ALT.

Too Much Information Can Be Too Much for Learning Eciently

Rolf Wiehagen, Thomas Zeugmann, Rolf Wiehagen, 1992 .