ML Anthology

ICML 1991

128 papers

A Computational Model of Acquisition for Children's Addtion Strategies Randolph M. Jones, Kurt VanLehn
A Constraint-Motivated Model of Lexical Acquisition Craig S. Miller, John E. Laird
A Domain-Independent Framework for Effective Experimentation in Planning Yolanda Gil
A Goal-Based Approach to Intelligent Information Retrieval Ashwin Ram, Lawrence Hunter
A Hybrid Approach to Guaranteed Effective Control Strategies Jonathan Gratch, Gerald DeJong
A Hybrid Method for Feature Generation Tom Fawcett, Paul E. Utgoff
A Knowledge-Intensive Approach to Learning Relational Concepts Michael J. Pazzani, Clifford Brunk, Glenn Silverstein
A Method for Multistrategy Task-Adaptive Learning Based on Plausible Justifications Gheorghe Tecuci, Ryszard S. Michalski
A Neural Network Approach to Constructive Induction Dit-Yan Yeung
A Probabilistic Retrieval Scheme for Cluster-Based Adaptive Information Retrieval Jay N. Bhuyan, Vijay V. Raghavan
A Prototype Based Symbolic Concept Learning System Michael de la Maza
A Smallest Generalization Step Strategy Claire Nedellec
A Study of How Domain Knowledge Improves Knowledge-Based Learning Systems Bradley L. Whitehall, Stephen C. Y. Lu
A Transformational Approach to Constructive Induction James P. Callan, Paul E. Utgoff
Abstracting Concepts with Inverse Resolution Attilio Giordana, Lorenza Saitta, Davide Roverso
Adaptive Pattern-Oriented Chess Robert Levinson, Richard Snyder
AIMS: An Adaptive Interactive Modeling System for Supporting Engineering Decision Making David K. Tcheng, Bruce L. Lambert, Stephen C. Y. Lu, Larry A. Rendell
An Enhancer for Reactive Plans Diana F. Gordon
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An Investigation of Noise-Tolerant Relational Concept Learning Algorithms Clifford Brunk, Michael J. Pazzani
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Babel: A Psychologically Plausible Cross-Linguistic Model of Lexical and Syntactic Acquisition Rick Kazman
Classification Trees for Information Retrieval Stuart L. Crawford, Robert M. Fung, Lee A. Appelbaum, Richard M. Tong
Combining Evidence of Deep and Surface Similarity Douglas H. Fisher, Jungsoon P. Yoo
Comparing Stochastic Planning to the Acquisition of Increasingly Permissive Plans Scott W. Bennett, Gerald DeJong
Comparison of Methods Based on Inverse Resolution Xiaofeng Ling, Malur Aji Narayan
Completeness for Inductive Procedures Céline Rouveirol
Complexity and Cooperation in Q-Learning Steven D. Whitehead
Computer Modelling of Acquisition Orders in Child Language Sheldon Nicholl, David C. Wilkins
Conceptual Clustering and Exploratory Data Analysis Gautam Biswas, Jerry B. Weinberg, Qian Yang, Glenn R. Koller
Constraints on Predicate Invention Rüdiger Wirth, Paul O'Rorke
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Constructive Induction in Knowledge-Based Neural Networks Geoffrey G. Towell, Mark W. Craven, Jude W. Shavlik
Constructive Induction in Theory Refinement Raymond J. Mooney, Dirk Ourston
Constructive Induction of M-of-N Terms Patrick M. Murphy, Michael J. Pazzani
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Constructive Induction on Symbolic Features Bing Leng, Bruce G. Buchanan
Continous Conceptual Set Covering: Learning Robot Operators from Examples Carl Myers Kadie
Database Consistency via Inductive Learning Jeffrey C. Schlimmer
Decision Tree Induction of 3-D Manufacturing Features Larry Watanabe, Sudhakar Yerramareddy
Decision-Theoretic Learning in an Action System Matthew Brand
Design Integrated Learning Systems for Engineering Design Yoram Reich
Design Rationale Capture as Knowledge Acquisition Thomas R. Gruber, Catherine Baudin, John H. Boose, Jay Webber
Determinate Literals in Inductive Logic Programming J. Ross Quinlan
Discovering Production Rules with Higher Order Neural Networks Adam Kowalczyk, Herman L. Ferrá, Ken Gardiner
Discovering Regularities from Large Knowledge Bases Wei-Min Shen
Efficient Learning of Logic Programs with Non-Determinant, Non-Discriminating Literals Boonserm Kijsirikul, Masayuki Numao, Masamichi Shimura
Experiments in Non-Monotonic Learning Michael Bain
Feature Construction in Structural Decision Trees Larry Watanabe, Larry A. Rendell
First-Order Theory Revision Bradley L. Richards, Raymond J. Mooney
Fringe-like Feature Construction: A Comparative Study and a Unifying Scheme Der-Shung Yang, Larry A. Rendell, Gunnar Blix
Generating Error Candidates for Assigning Blame in a Knowledge Base Michael A. Weintraub, Tom Bylander
Identifying Cost Effective Boundaries of Operationality Jungsoon P. Yoo, Douglas H. Fisher
Improving Learning Using Causality and Abduction Marco Botta, S. Ravotto, Lorenza Saitta, S. B. Sperotto
Improving Recognition Effectiveness of Noisy Texture Concepts Peter Pachowicz, Jerzy W. Bala
Improving Shared Rules in Multiple Category Domain Theories Dirk Ourston, Raymond J. Mooney
Improving the Performance of Inconsistent Knowledge Bases via Combined Optimization Method Yong Ma, David C. Wilkins
Incremental Constructive Induction: An Instance-Based Approach David W. Aha
Incremental Development of Complex Behaviors Mark B. Ring
Incremental Learning in a Probalistic Information Retrieval System A. Goker, Thomas Leo McCluskey
Incremental Refinement of Approximate Domain Theories Ronen Feldman, Alberto M. Segre, Moshe Koppel
Inducing Temporal Fault Diagnostic Rules from a Qualitative Model C. Feng
Informed Pruning in Constructive Induction George Drastal
Integrity Constraints and Interactive Concept-Learning Luc De Raedt, Maurice Bruynooghe, Bern Martens
Internal World Models and Supervised Learning Michael I. Jordan, David E. Rumelhart
Is It a Pocket or a Purse? Tighly Coupled Theory and Data Driven Learing Edward J. Wisniewski, Douglas L. Medin
Knowledge Acquisition Combining Analytical and Empirrcal Techniques Mario Martín, Ramon Sangüesa, Ulises Cortés
Knowledge Compilation to Speed up Numerical Optimization Giuseppe Cerbone, Thomas G. Dietterich
Knowledge Refinement Using a High Level, Non-Technical Vocabulary Eric K. Jones
Knowledge-Based Equation Discovery in Engineering Domains R. Bharat Rao, Stephen C. Y. Lu, Robert E. Stepp
Learning a Cost-Sensitive Internal Representation for Reinforcement Learning Ming Tan
Learning a Set of Primitive Actions with an Uninterpreted Sensorimotor Apparatus David R. Pierce
Learning Analytical Knowledge About VLSI-Design from Observation Jürgen Herrmann
Learning Concepts by Synthesizing Minimal Threshold Gate Networks Arlindo L. Oliveira, Alberto L. Sangiovanni-Vincentelli
Learning Constrained Atoms C. David Page Jr., Alan M. Frisch
Learning Football Evaluation for a Walking Robot Goang-Tay Hsu, Reid G. Simmons
Learning from Deliberated Reactivity Bruce Krulwich
Learning in Intelligent Information Retrieval David D. Lewis
Learning Physics via Explanation-Based Learning of Correctness and Analogical Search Control Kurt VanLehn, Randolph M. Jones
Learning Polynomial Functions by Feature Construction Richard S. Sutton, Christopher J. Matheus
Learning Qualitative Models of Dynamic Systems Ivan Bratko, Stephen H. Muggleton, Alen Varsek
Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL Saso Dzeroski, Nada Lavrac
Learning Search Control Rules for Planning: An Inductive Approach Christopher Leckie, Ingrid Zukerman
Learning Spatial Relations from Images Kazuo Hiraki, John H. Gennari, Yoshinobu Yamamoto, Yuichiro Anzai
Learning Stochastic Motifs from Genetic Sequences Kenji Yamanishi, Akihiko Konagaya
Learning the Persistence of Actions in Reactive Control Rules Helen G. Cobb, John J. Grefenstette
Learning to Avoid Obstacles Through Reinforcement José del R. Millán, Carme Torras
Learning to Select a Model in a Changing World Mieczyslaw M. Kokar, Spyros A. Reveliotis
Learning Variable Descriptors for Applying Heuristics Across CSP Problems David S. Day
Learning with Incrutable Theories Prasad Tadepalli
Learning Words from Context Peter M. Hastings, Steven L. Lytinen, Robert K. Lindsay
Machine Learning for Nondestructive Evaluation Paul O'Rorke, Steven Morris, Michael Amirfathi, William E. Bond, Daniel C. St. Clair
Machine Learning in Engineering Automation Steve A. Chien, Bradley L. Whitehall, Thomas G. Dietterich, Richard J. Doyle, Brian Falkenhainer, James Garrett, Stephen C. Y. Lu
Machine Learning in the Combination of Expert Opinion Approach to IR Paul Thompson
Megainduction: A Test Flight Jason Catlett
Model Revision: A Theory of Incremental Model Learning Ashok K. Goel
Modeling the Acquisition and Improvement of Motor Skkills Wayne Iba
Noise-Resistant Classification Leonid V. Belyaev, Loretta P. Falcone
On Becoming Decreasingly Reactive: Learning to Deliberate Minimally Steve A. Chien, Melinda T. Gervasio, Gerald DeJong
On the Effect of Instance Representation on Generalization Sharad Saxena
Opportunistic Constructive Induction Gregg H. Gunsch, Larry A. Rendell
Planning by Incremental Dynamic Programming Richard S. Sutton
Predicting Actions from Induction on past Performance Steven Walczak
Probabilistic Concept Formation in Relational Domains John A. Allen, Kevin Thompson
Probabilistic Evaluating of Bias for Learning Systems Marie desJardins
Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning Carl Myers Kadie
Query Formulation Through Knowledge Acquisition Sanjiv K. Bhatia, Jitender S. Deogun, Vijay V. Raghavan
Query Learning Using an ANN with Adaptive Architecture K. L. Kwok
Refinement of Approximate Reasoning-Based Controllers by Reinforcement Learning Hamid R. Berenji
Refining Domain Theories Expressed as Finite-State Automata Richard Maclin, Jude W. Shavlik
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Relational Clichés: Constraining Induction During Relational Learning Glenn Silverstein, Michael J. Pazzani
Relations, Knowledge and Empirical Learning Harish Ragavan, Larry A. Rendell
Revising Relational Domain Theories James Wogulis
Revision Cost for Theory Refinement Rei Hamakawa
Revision of Reduced Theories Xiaofeng Ling, Marco Valtorta
Scaling Reinforcement Learning Techniques via Modularity Lambert E. Wixson
Scaling Reinforcement Learning to Robotics by Exploiting the Subsumption Architecture Sridhar Mahadevan, Jonathan Connell
Self-Improvement Based on Reinforcement Learning, Planning and Teaching Long Ji Lin
Simulating Stages of Human Cognitive Development with Connectionist Models Thomas R. Shultz
The Acquisition of Human Planning Expertise Pat Langley, John A. Allen
The Blind Leading the Blind: Mutual Refinement of Approximate Theories Smadar Kedar, John L. Bresina, C. Lisa Dent
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The Consistent Concept Axiom Zhaogang Qian, Keki B. Irani
The DUCTOR: A Theory Revision System for Propositional Domains Timothy Cain
The Flexibility of Speculative Refinement Susan Craw, Derek H. Sleeman
The Generality of Overgenerality William W. Cohen
The Importance of Causal Structure and Facts in Evaluating Explanations Mary Gick, Stan Matwin
The Need for Constructive Induction Christopher J. Matheus
Transfer of Learning Across Compositions of Sequentail Tasks Satinder P. Singh
Using Background Knowledge in Concept Formation Kevin Thompson, Pat Langley, Wayne Iba
Using Inverse Resolution to Learn Relations from Experiments David Humme, Claude Sammut
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Variability Bias and Category Learning Joel D. Martin, Dorrit Billman
Variable Resolution Dynamic Programming Andrew W. Moore