John Case

Affiliations:
  • University of Delaware, Newark, USA


According to our database1, John Case authored at least 100 papers between 1971 and 2020.

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Bibliography

2020
Leveraging Iterative Design of Experiments to Innovate in a High-Risk Production Environment: A US Army Aviation Case Study.
Proceedings of the IEEE International Systems Conference, 2020

2018
Effectivity questions for Kleene's recursion theorem.
Theor. Comput. Sci., 2018

2017
Connections Between Inductive Inference and Machine Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

2016
Topological separations in inductive inference.
Theor. Comput. Sci., 2016

Strongly non-U-shaped language learning results by general techniques.
Inf. Comput., 2016

Non-Obfuscated Unprovable Programs & Many Resultant Subtleties.
Log. Methods Comput. Sci., 2016

Program Size Complexity of Correction Grammars in the Ershov Hierarchy.
Proceedings of the Pursuit of the Universal - 12th Conference on Computability in Europe, 2016

2014
Automatic learners with feedback queries.
J. Comput. Syst. Sci., 2014

2013
On the Necessity of U-Shaped Learning.
Top. Cogn. Sci., 2013

Memory-limited non-U-shaped learning with solved open problems.
Theor. Comput. Sci., 2013

Automatic functions, linear time and learning.
Log. Methods Comput. Sci., 2013

Beyond Rogers' Non-constructively Computable Function.
Proceedings of the Nature of Computation. Logic, Algorithms, Applications, 2013

2012
Program Self-Reference in Constructive Scott Subdomains.
Theory Comput. Syst., 2012

Algorithmic Scientific Inference: Within Our Computable Expected Reality?
Int. J. Unconv. Comput., 2012

Learning secrets interactively. Dynamic modeling in inductive inference.
Inf. Comput., 2012

Automatic learning of subclasses of pattern languages.
Inf. Comput., 2012

2011
Rice and Rice-Shapiro Theorems for transfinite correction grammars.
Math. Log. Q., 2011

Optimal language learning from positive data.
Inf. Comput., 2011

Properties Complementary to Program Self-Reference.
Fundam. Informaticae, 2011

Measuring Learning Complexity with Criteria Epitomizers.
Proceedings of the 28th International Symposium on Theoretical Aspects of Computer Science, 2011

2010
Connections Between Inductive Inference and Machine Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Iterative learning of simple external contextual languages.
Theor. Comput. Sci., 2010

Strongly Non-U-Shaped Learning Results by General Techniques.
Proceedings of the COLT 2010, 2010

Solutions to Open Questions for Non-U-Shaped Learning with Memory Limitations.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009
Parallelism increases iterative learning power.
Theor. Comput. Sci., 2009

Characterizing Programming Systems Allowing Program Self-Reference.
Theory Comput. Syst., 2009

Resource Restricted Computability Theoretic Learning: Illustrative Topics and Problems.
Theory Comput. Syst., 2009

Learning correction grammars.
J. Symb. Log., 2009

Independence Results for <i>n</i>-Ary Recursion Theorems.
Proceedings of the Fundamentals of Computation Theory, 17th International Symposium, 2009

Difficulties in Forcing Fairness of Polynomial Time Inductive Inference.
Proceedings of the Algorithmic Learning Theory, 20th International Conference, 2009

2008
Foreword.
Theor. Comput. Sci., 2008

U-shaped, iterative, and iterative-with-counter learning.
Mach. Learn., 2008

Non-U-shaped vacillatory and team learning.
J. Comput. Syst. Sci., 2008

When unlearning helps.
Inf. Comput., 2008

Optimal Language Learning.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

Dynamic Modeling in Inductive Inference.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

Dynamically Delayed Postdictive Completeness and Consistency in Learning.
Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007
Foreword.
Theor. Comput. Sci., 2007

Results on memory-limited U-shaped learning.
Inf. Comput., 2007

Cautious virus detection in the extreme.
Proceedings of the 2007 Workshop on Programming Languages and Analysis for Security, 2007

Feasible Iteration of Feasible Learning Functionals.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

2006
Learning a subclass of regular patterns in polynomial time.
Theor. Comput. Sci., 2006

Identifying Clusters from Positive Data.
SIAM J. Comput., 2006

Generality's price: Inescapable deficiencies in machine-learned programs.
Ann. Pure Appl. Log., 2006

Memory-Limited U-Shaped Learning.
Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005
On learning to coordinate: random bits help, insightful normal forms, and competency isomorphisms.
J. Comput. Syst. Sci., 2005

2004
Off-Loading Memory to the Environment: A Quantitative Example.
Minds Mach., 2004

Parsimony hierarchies for inductive inference.
J. Symb. Log., 2004

Robust learning--rich and poor.
J. Comput. Syst. Sci., 2004

On the classification of recursive languages.
Inf. Comput., 2004

A Polynomial Time Learner for a Subclass of Regular Patterns
Electron. Colloquium Comput. Complex., 2004

Computing Entropy for Ortholog Detection.
Proceedings of the International Conference on Computational Intelligence, 2004

2002
Control structures in hypothesis spaces: the influence on learning.
Theor. Comput. Sci., 2002

Learning to Win Process-Control Games Watching Game-Masters.
Inf. Comput., 2002

2001
Synthesizing noise-tolerant language learners.
Theor. Comput. Sci., 2001

Predictive learning models for concept drift.
Theor. Comput. Sci., 2001

Costs of general purpose learning.
Theor. Comput. Sci., 2001

Synthesizing Learners Tolerating Computable Noisy Data.
J. Comput. Syst. Sci., 2001

Lattice computers for approximating Euclidean space.
J. ACM, 2001

Divide and Conquer Machine Learning for a Genomics Analogy Problem (Progress Report).
Proceedings of the Discovery Science, 4th International Conference, DS 2001, Washington, 2001

2000
Vacillatory and BC learning on noisy data.
Theor. Comput. Sci., 2000

Robust Learning Aided by Context.
J. Comput. Syst. Sci., 2000

Unlearning Helps.
Proceedings of the Automata, Languages and Programming, 27th International Colloquium, 2000

1999
The Power of Vacillation in Language Learning.
SIAM J. Comput., 1999

Maximal Machine Learnable Classes.
J. Comput. Syst. Sci., 1999

Incremental Concept Learning for Bounded Data Mining.
Inf. Comput., 1999

The Synthesis of Language Learners.
Inf. Comput., 1999

1997
Learning Recursive Functions from Approximations.
J. Comput. Syst. Sci., 1997

On the Classification of Computable Languages.
Proceedings of the STACS 97, 14th Annual Symposium on Theoretical Aspects of Computer Science, Lübeck, Germany, February 27, 1997

1996
Anomalous Learning Helps Succinctness.
Theor. Comput. Sci., 1996

Learnability: Admissible, Co-Finite, and Hypersimple Languages.
J. Comput. Syst. Sci., 1996

Machine Induction Without Revolutionary Changes in Hypothesis Size.
Inf. Comput., 1996

Synthesizing Enumeration Techniques for Language Learning.
Proceedings of the Ninth Annual Conference on Computational Learning Theory, 1996

1995
Complexity Issues for Vacillatory Function Identification
Inf. Comput., February, 1995

Language Learning with Some Negative Information.
J. Comput. Syst. Sci., 1995

Not-So-Nearly-Minimal-Size Program Inference.
Proceedings of the Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report, 1995

Machine Induction Without Revolutionary Paradigm Shifts.
Proceedings of the Algorithmic Learning Theory, 6th International Conference, 1995

1994
Refinements of inductive inference by Popperian and reliable machines.
Kybernetika, 1994

Machine Learning of Higher-Order Programs.
J. Symb. Log., 1994

Spatial/kinematic domain and lattice computers.
J. Exp. Theor. Artif. Intell., 1994

Infinitary self-reference in learning theory.
J. Exp. Theor. Artif. Intell., 1994

Vacillatory Learning of Nearly Minimal Size Grammars.
J. Comput. Syst. Sci., 1994

Learning with Higher Order Additional Information.
Proceedings of the Algorithmic Learning Theory, 1994

Subrecursive programming systems - complexity and succinctness.
Progress in theoretical computer science, Birkhäuser, ISBN: 978-3-7643-3767-4, 1994

1992
Strong separation of learning classes.
J. Exp. Theor. Artif. Intell., 1992

On Learning Limiting Programs.
Int. J. Found. Comput. Sci., 1992

Representing the Spatial/Kinematic Domain and Lattice Computers.
Proceedings of the Analogical and Inductive Inference, 1992

1991
Effectivizing Inseparability.
Math. Log. Q., 1991

1990
Optimally Representing Euclidean Space Discretely for Analogically Simulating Physical Phenomena.
Proceedings of the Foundations of Software Technology and Theoretical Computer Science, 1990

Anomalous Learning Helps Succinctness (Extended Abstract).
Proceedings of the Algorithmic Learning Theory, First International Workshop, 1990

1989
Convergence to Nearly Minimal Size Grammars by Vacillating Learning Machines.
Proceedings of the Second Annual Workshop on Computational Learning Theory, 1989

1988
The Power of Vacillation.
Proceedings of the First Annual Workshop on Computational Learning Theory, 1988

1983
Comparison of Identification Criteria for Machine Inductive Inference.
Theor. Comput. Sci., 1983

Pseudo-Extending Computable Functions
Inf. Control., 1983

1982
Machine Inductive Inference and Language Identification.
Proceedings of the Automata, 1982

1978
The Complexity of Total Order Structures.
J. Comput. Syst. Sci., 1978

Anomaly Hierarchies of Mechanized Inductive Inference
Proceedings of the 10th Annual ACM Symposium on Theory of Computing, 1978

1976
Sortability and Extensibility of the Graphs of Recursively Enumerable Partial and Total Orders.
Math. Log. Q., 1976

1974
Periodicity in Generations of Automata.
Math. Syst. Theory, 1974

1971
A Note on Degrees of Self-Describing Turing Machines.
J. ACM, 1971


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