1987 | | | **Debugging a DAG Efficiently** - *D. Angluin* |

| | | **Some Notes on Chernoff Bounds** - *R. H. Sloan* |

| | | **Semi-supervised learning** - *L. Pitt and R. Board* |

| | | **Phoneme Recognition Using Time-Delay Neural Networks** - *A. Waibel, T. Hanazawa, G. Ginton and K. Shikano* |

| | | **A Version Space Approach to Learning Context-free Grammars** - *Kurt Vanlehn and William Ball* |

| | | **Simplifying Decision Trees** - *J. R. Quinlan* |

| | | **Knowledge Acquisition Via Incremental Conceptual Clustering** - *Douglas H. Fisher* |

| | | **Automatic learning, rule extraction and generalization** - *J. Denker, D. Schwartz, B. Wittner, S. Solla, R. Howard, L. Jackel and J. Hopfield* |

| | | **Inferring parsers of context-free languages from structural examples** - *Y. Sakakibara* |

| | | **The Asymptotic Theory of Extreme Order Statistics** - *Janos Galambos* |

| | | **Neural Darwinism - The Theory of Neuronal Group Selection** - *G. M. Edelman* |

| | | **A Review of the Fourth International Workshop on Machine Learning** - *R. P. Hall, B. Falkenhainer, N. Flann, S. Hampson, R. Reinke, J. Shrager, M. H. Sims and P. Tadepalli* |

| | | **Univresal sequential Coding of Single Messages** - *Y. M. Shtarkov* |

| | | **Learning Syntax by Automata Induction** - *Robert C. Berwick and Sam Pilato* |

| | | **Applying Valiant's Learning Framework to AI Concept Learning Problems** - *D. Haussler* |

| | | **Theory Change via View Application in Instructionless Learning** - *Jeff Shrager* |

| | | **Learning Functions from Examples** - *B. K. Natarajan* |

| | | **On the learnability of Boolean formulae** - *M. Kearns, M. Li, L. Pitt and L. Valiant* |

| | | **Analogical and Inductive Inference, International Workshop AII '86. Wendisch-Rietz, GDR, October 1986, Proceedings** - *K. P. Jantke* |

| | | **On Language and Connectionism: Analysis of a Parallel Distributed Processing Model of Language Acquisition** - *S. Pinker and A. Prince* |

| | | **Learning Decision Lists** - *Ronald L. Rivest* |

| | | **Classifier Systems and the Animat Problem** - *Stewart W. Wilson* |

| | | **Language Learning by Automata Induction** - *R. C. Berwick* |

| | | **Machine Learning and Concept Formation** - *P. Langley* |

| | | **Application of a General Learning Algorithm to the Control of Robotic Manipulators** - *W. T. Miller, F. H. Glanz and L. G. Kraft* |

| | | **Inductive inference of logic programs based on algebraic semantics** - *Y. Sakakibara* |

| | | **Testing and inductive inference: abstract approaches** - *J. Cherniavsky and R. Statman* |

| | | **A Mean Field Theory Learning Algorithm for Neural Networks** - *C. Peterson and J. R. Anderson* |

| | | **Epsilon-nets and Simplex Range Queries** - *D. Haussler and E. Welzl* |

| | | **On convergence to the truth and nothing but the truth** - *K. Kelly and C. Glymour* |

| | | **Learning one-counter languages in polynomial time** - *P. Berman and R. Roos* |

| | | **Shift of Bias for Inductive Concept Learning** - *P. Utgoff* |

| | | **Research Papers in Machine Learning** - *P. Langley* |

| | | **On learning Boolean functions** - *B. K. Natarajan* |

| | | **Learning in permutation groups (extended abstract)** - *U. Feige and A. Shamir* |

| | | **Radial Basis Functions for Multivariable Interpolation: A Review** - *M. J. D. Powell* |

| | | **Efficient algorithms with neural networks behavior** - *S. Omohundro* |

| | | **Diversity-based inference of finite automata** - *R. L. Rivest and R. E. Schapire* |

| | | **Scaling relationships in back-propagation learning: dependence on training set size** - *G. Tesauro* |

| | | **Inductive Inference** - *Dana Angluin and Carl H. Smith* |

| | | **Machine Learning and Grammar Induction** - *P. Langley* |

| | | **Algorithms in Combinatorial Geometry** - *H. Edelsbrunner* |

| | | **Inference of visible simple assignment automata with planned experiments** - *R. Rivest and R. Schapire* |

| | | **Experiments with Incremental Concept Formation: UNIMEM** - *Michael Lebowitz* |

| | | **Inferring Parsers of Context Free Languages from Structural Examples** - *Y. Sakakibara* |

| January | | **Learning One Subprocedure per Lesson** - *K. VanLehn* |

| February | | **Parallel Networks that Learn to Pronounce English Text** - *T. J. Sejnowski and C. R. Rosenberg* |

| March | | **Stability and Looping in Connectionist Models with Assymmetric Weights** - *S. Porat* |

| April | | **An Introduction to Computing with Neural Nets** - *R. P. Lippmann* |

| | | **Occam's Razor** - *A. Blumer, A. Ehrenfeucht, D. Haussler and M. K. Warmuth* |

| | | **Minimum Information Estimation of Structure** - *G. W. Hart* |

| May | | **Combining Cross-Validation and Search** - *C. J. C. H. Watkins* |

| | | **Induction in Noisy Domains** - *P. Clark and T. Niblett* |

| | | **Constructing Decision Trees in Noisy Domains** - *T. Niblett* |

| | | **Assistant 86: A Knowledge-Elicitation Tool for Sophisticated Users** - *B I. K. Cestnik and I. Bratko* |

| | | **Review of Five Empirical Learning Systems Within a Proposed Schemata** - *M. Gams and N. Lavrac* |

| June | | **Learning in a Layered Network with many Fixed-Function Hidden Nodes** - *N. Littlestone* |

| | | **Bias, Version Spaces, and Valiant's Learning Framework** - *D. Haussler* |

| | | **A New Approach to Unsupervised Learning in Deterministic Environments** - *R. L. Rivest and R. E. Schapire* |

| | | **Recent Results on Boolean Concept Learning** - *M. Kearns, M. Li, L. Pitt and L. Valiant* |

| | | **Learning by Experimentation** - *J. G. Carbonell and Y. Gil* |

| July | | **A Mechanism for Early Piagetian Learning** - *G. L. Drescher* |

| | | **Complexity of Connectionist Learning with Various Node Functions** - *J. S. Judd* |

| | | **A Physiological Basis for a Theory of Synapse Modification** - *M. F. Bear, L. N. Cooper and F. F. Ebner* |

| August | | **Learning k-term DNF Formulas using Queries and Counterexamples** - *D. Angluin* |

| | | **Identification of Pattern Languages from Examples and Queries** - *A. Marron and K. Ko* |

| | | **Learning k-Bounded Context-Free Grammars** - *D. Angluin* |

| September | | **Convergence Results in the Hopfield Model** - *J. Kómlos and R. Paturi* |

| | | **SOAR: An architecture for General Intelligence** - *J. E. Laird, A. Newell and P. S. Rosenbloom* |

| November | | **Learning Regular Sets from Queries and Counterexamples** - *D. Angluin* |

| December | | **Polynomially Sized Boolean Circuits are not Learnable** - *D. Beaver* |

| | | **Learning propositional Horn sentences with hints** - *D. Angluin* |