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7. ALT 1996: Sydney, Australia
- Setsuo Arikawa, Arun Sharma:
Algorithmic Learning Theory, 7th International Workshop, ALT '96, Sydney, Australia, October 23-25, 1996, Proceedings. Lecture Notes in Computer Science 1160, Springer 1996, ISBN 3-540-61863-5 - Leslie G. Valiant:
Managing Complexity in Neurodial Circuits. 1-11 - Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka:
Learnability of Exclusive-Or Expansion Based on Monotone DNF Formulas. 12-25 - Philip M. Long:
Improved Bounds about On-line Learning of Smooth Functions of a Single Variable. 26-36 - Atsuyoshi Nakamura:
Query Learning of Bounded-Width OBDDs. 37-50 - Hans Kleine Büning, Theodor Lettmann:
Learning a Representation for Optimizable Formulas. 51-58 - Arlindo L. Oliveira
, Stephen Edwards:
Limits of Exact Algorithms For Inference of Minimum Size Finite State Machines. 59-66 - Paul M. B. Vitányi:
Genetic Fitness Optimization Using Rapidly Mixing Markov Chains. 67-82 - Rohan A. Baxter, Jonathan J. Oliver:
The Kindest Cut: Minimum Message Length Segmentation. 83-90 - R. A. Pearson, E. K. T. Smith:
Reducing Complexity of Decision Trees with Two Variable Tests. 91-99 - Vikraman Arvind, N. V. Vinodchandran:
The Complexity of Exactly Learning Algebraic Concepts. (Extended Abstract). 100-112 - Amr F. Fahmy, Robert S. Roos:
Efficient Learning of Real Time Two-Counter Automata (Extended Abstract). 113-126 - Nada Lavrac, Dragan Gamberger, Peter D. Turney:
Cost-Sensitive Feature Reduction Applied to a Hybrid Genetic Algorithm. 127-134 - Selwyn Piramuthu:
Effects of Feature Selection with 'Blurring' on NeuroFuzzy Systems. 135-142 - J. Ross Quinlan:
Boosting First-Order Learning. 143-155 - Janis Barzdins, Ugis Sarkans:
Incorporating Hypothetical Knowledge into the Process of Inductive Synthesis. 156-168 - Lionel Martin, Christel Vrain:
Induction of Constraint Logic Programs. 169-176 - Noriko Sugimoto, Kouichi Hirata
, Hiroki Ishizaka:
Constructive Learning of Translations Based on Dictionaries. 177-184 - Jianguo Lu, Jun Arima:
Inductive Logic Programming Beyond Logical Implication. 185-198 - Dragan Gamberger, Nada Lavrac, Saso Dzeroski
:
Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois. 199-212 - David L. Dowe, Jonathan J. Oliver
, Chris S. Wallace:
MML Estimation of the Parameters of the Sherical Fisher Distribution. 213-227 - Steffen Lange, Rolf Wiehagen, Thomas Zeugmann:
Learning by Erasing. 228-241 - Sanjay Jain, Efim B. Kinber, Rolf Wiehagen:
On Learning and Co-learning of Minimal Programs. 242-255 - Takeshi Shinohara, Hiroki Arimura:
Inductive Inference of Unbounded Unions of Pattern Languages from Positive Data. 256-271 - M. R. K. Krishna Rao:
A Class of Prolog Programs Inferable from Positive Data. 272-284 - John Case, Sanjay Jain, Frank Stephan:
Vacillatory and BC Learning on Noisy Data. 285-298 - Andris Ambainis, Rusins Freivalds:
Transformations that Preserve Learnability. 299-311 - Juris Viksna:
Probabilitic Limit Identification up to "Small" Sets. 312-324 - Gunter Grieser:
Reflecting Inductive Inference Machines and Its Improvement by Therapy. 325-336

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