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| Image Color Constancy Using EM and Cached Statistics - Charles Rosenberg - 2000 |
| Implementation Issues in the Fourier Transform Algorithm - Yishay Mansour and Sigal Sahar - 2000 |
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| An Improved On-line Algorithm for Learning Linear Evaluation Functions - Peter Auer - 2000 |
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| Improve the Learning of Subsequential Transducers by Using Alignments and Dictionaries - Juan Miguel Vilar - 2000 |
| Improving accuracy of incorrect domain theories - L. Asker - 1994 |
| Improving Algorithms for Boosting - Javed A. Aslam - 2000 |
| Improving Example-Guided Unfolding - Henrik Boström - 1993 |
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| Improving Knowledge Discovery Using Domain Knowledge in Unsupervised Learning - Javier Béjar - 2000 |
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| Improving Performance in Neural Networks Using a Boosting Algorithm - H. Drucker, R. Schapire and P. Simard - 1992 |
| Improving Probabilistic Grammatical Inference Core Algorithms with Post-Processing Techniques - Franck Thollard - 2001 |
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| Improving Short-Text Classification Using Unlabeled Background Knowledge to Assess Document Similarity - Sarah Zelikovitz and Haym Hirsh - 2000 |
| Improving support vector machine classifiers by modifying kernel functions - S. Amari and S. Wu - 1999 |
| Improving Term Extraction by System Combination Using Boosting - Jordi Vivaldi, Llu\'ıs Màrquez and Horacio Rodr\'ıguez - 2001 |
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| Improving the Robustness and Encoding Complexity of Behavioural Clones - Rui Camacho and Pavel Brazdil - 2001 |
| Inclusion is Undecidable for Pattern Languages - Tao Jiang, Arto Salomaa, Kai Salomaa and Sheng Yu - 1993 |
| Inclusion problems in parallel learning and games - Martin Kummer and Frank Stephan - 1996 |
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| Incremental Induction of Decision Trees - Paul E. Utgoff - 1989 |
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| Incremental Maximization of Non-Instance-Averaging Utility Functions with Applications to Knowledge Discovery Problems - Tobias Scheffer and Stefan Wrobel - 2001 |
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| Induction by Enumeration - Eric Martin and Daniel Osherson - November 2001 |
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| Induction of Qualitative Trees - Dorian Suc and Ivan Bratko - 2001 |
| Induction of Recursive Bayesian Classifiers - Pat Langley - 1993 |
| The Induction of Temporal Grammatical Rules from Multivariate Time Series - Gabriela Guimarães - 2000 |
| Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning - Raymond J. Mooney - 1993 |
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| Inferring Answers to Queries - William I. Gasarch and Andrew C. Y. Lee - 1997 |
| Inferring a Rewriting System from Examples - Yasuhito Mukouchi, Ikuyo Yamue and Masako Sato - 1998 |
| Inferring a system from examples with time passage - Yasuhito Mukouchi - 1997 |
| Inferring a Tree from Walks - O. Maruyama and S. Miyano - December 1991 |
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| Inferring Decision Trees Using the Minimum Description Length Principle - J. R. Quinlan and R. L. Rivest - March 1989 |
| Inferring Deterministic Linear Languages - Colin de la Higuera and Jose Oncina - 2002 |
| Inferring finite automata with stochastic output functions and an application to map learning - Thomas Dean, Dana Angluin, Kenneth Basye, Sean Engelson, Leslie Kaelbling, Evangelos Kokkevis and Oded Maron - 1995 |
| Inferring grammars by means of profiles: a unifying view - S. Crespi-Reghizzi and D. Mandrioli - 1980 |
| Inferring graphs from walks - J. A. Aslam and R. L. Rivest - 1990 |
| Inferring Graphs from Walks - J. A. Aslam - January 1992 |
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| Inferring parsers of context-free languages from structural examples - Y. Sakakibara - 1987 |
| Inferring Parsers of Context Free Languages from Structural Examples - Y. Sakakibara - 1987 |
| Inferring reduced ordered decision graphs of minimum decision length - Arlindo L. Oliveira and Alberto Sangiovanni-Vincentelli - 1995 |
| Inferring regular languages in polynomial update time - J. Oncina and P. Garcia - 1992 |
| Inferring stochastic regular grammars with recurrent neural networks - Rafael C. Carrasco, Mikel L. Forcada and Laureano Santamar\'ıa - 1996 |
| Inferring Subclasses of Contextual Languages - J. D. Emerald, K. G. Subramanian and D. G. Thomas - 2000 |
| Inferring the structure of a Markov chain from its output - S. Rudich - October 1985 |
| Inferring Unions of two Pattern Languages - Takeshi Shinohara - 1983 |
| Infinitary Self-Reference in Learning Theory - J. Case - 1994 |
| An Infinite Class of Functions Identifiable Using Minimal Programs in all Kolmogorov Numberings - Sanjay Jain - 1995 |
| Infinite-Horizon Policy-Gradient Estimation - J. Baxter and P. L. Bartlett - 2001 |
| Information-Based Evaluation Criterion for Classifier's Performance - Igor Kononenko and Ivan Bratko - 1991 |
| Information bounds for the risk of Bayesian predictions and the redundancy of universal codes - A. Barron, B. Clarke and D. Haussler - January 1993 |
| Information Filtering: Selection Mechanisms in Learning Systems - Shaul Markovitch and Paul D. Scott - 1993 |
| Information Geometry of the EM and em Algorithms for Neural Networks - Shun-ichi Amari - 1995 |
| An Information Measure for Classification - C. S. Wallace and D. M. Boulton - 1968 |
| Information-theoretical aspects of inductive and deductive inference - S. Watanabe - 1960 |
| An information-theoretic definition of similarity - Dekang Lin - 1998 |
| Information theory in probability, statistics, learning, and neural nets - Andrew R. Barron - 1997 |
| Informed parsimonious inference of prototypical genetic sequences - A. Milosavljevi'c, D. Haussler and J. Jurka - 1989 |
| Initializing neural networks using decision trees - Arunava Banerji - 1997 |
| An Initial Study of an Adaptive Hierarchical Vision System - Marcus A. Maloof - 2000 |
| In Pursuit of Interesting Patterns with Undirected Discovery of Exception Rules - Einoshin Suzuki - 2001 |
| In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project - Gerhard Widmer - 2002 |
| Instance-Based Learning Algorithms - David W. Aha, Dennis Kibler and Marc K. Albert - 1991 |
| Instance-based utile distinctions for reinforcement learning with hidden state - R. Andrew McCallum - 1995 |
| Instance-family abstraction in memory-based language learning - Antal van den Bosch - 1999 |
| Instance Pruning as an Information Preserving Problem - Marc Sebban and Richard Nock - 2000 |
| Instance pruning techniques - D. Randall Wilson and Tony R. Martinez - 1997 |
| An Integrated Connectionist Approach to Reinforcement Learning for Robotic Control: The Advantages of Indexed Partitioning - Dean F. Hougen, Maria Gini and James Slagle - 2000 |
| An Integrated Framework for Empirical Discovery - Bernd Nordhausen and Pat Langley - 1993 |
| Integrating case-based learning and cognitive biases for machine learning of natural language - Claire Cardie - 1999 |
| Integrating feature construction with multiple classifiers in decision tree induction - Ricardo Vilalta and Larry Rendell - 1997 |
| Integrating Feature Extraction and Memory Search - Christopher Owens - 1993 |
| Integrating Models of Knowledge and Machine Learning - Jean-Gabriel Ganascia, J. Thomas and Philippe Laublet - 1993 |
| Integrating Quantitative and Qualitative Discovery: The ABACUS System - Brian C. Falkenhainer and Ryszard S. Michalski - 1986 |
| An Integration of Rule Induction and Exemplar-Based Learning for Graded Concepts - Jianping Zhang and Ryszard S. Michalski - 1995 |
| Interactive Concept-Learning and Constructive Induction by Analogy - Luc De Raedt and Maurice Bruynooghe - 1992 |
| An interactive knowledge transfer model and analysis of Mastermind game - K. Koyama and T. Lai - 1992 |
| An interference matching technique for inducing abstractions - F. Hayes-Roth and J. McDermott - 1978 |
| Intra-option learning about temporally abstract actions - Richard S. Sutton, Doina Precup and Satinder Singh - 1998 |
| The intrinsic complexity of language identification - Sanjay Jain and Arun Sharma - 1996 |
| Intrinsic Complexity of Learning Geometrical Concepts from Positive Data - Sanjay Jain and Efim Kinber - 2001 |
| Introducing statistical dependencies and structural constraints in variable-length sequence models - Sabine Deligne, François Yvon and Frédéric Bimbot - 1996 |
| Introducing the Special Issue of Machine Learning Selected from Papers Presented at the 1997 Conference on Computational Learning Theory, COLT'97 - John Shawe-Taylor - 1999 |
| Introduction - Vasant Honavar and Colin de la Higuera - 2001 |
| Introduction - Judy A. Franklin, Tom M. Mitchell and Sebastian Thrun - 1996 |
| Introduction - Leslie Pack Kaelbling - 1996 |
| Introduction - David S. Touretzky - 1991 |
| Introduction - Satinder Singh - 2002 |
| Introduction - Jude Shavlik, Lawrence Hunter and David Searls - 1995 |
| Introduction: Cognitive Autonomy in Machine Discovery - Jan M. Żytkow - 1993 |
| Introduction: Special Issue on Computational Learning Theory - Leonard Pitt - 1990 |
| Introduction Structured Connectionist Systems - Alex Waibel - 1994 |
| Introduction to Algorithms - T. H. Cormen, C. E. Leiserson and R. L. Rivest - 1990 |
| An Introduction to Computational Learning Theory - Michael J. Kearns and Umesh V. Vazirani - 1994 |
| An Introduction to Computing with Neural Nets - R. P. Lippmann - April 1987 |
| An Introduction to Hidden Markov Models - L. R. Rabiner and B. H. Juang - January 1986 |
| An Introduction to Kolmogorov Complexity and Its Applications - M. Li and P. Vitányi - 1993 |
| An Introduction to Probability and its Applications - W. Feller - 1971 |
| An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods - Nello Cristianini and John Shawe-Taylor - 2000 |
| Introduction to the Abstracts of the Invited Talks Presented at ML92 Conference in Aberdeen, 1-3 July 1992 - D. Sleeman - 1994 |
| An Introduction to the Application of the Theory of Probabilistic Functions of a Markov Process to Automatic Speech Recognition - S. E. Levinson, L. R. Rabiner and M. M. Sondhi - April 1983 |
| An Introduction to Variational Methods for Graphical Models - Michael I. Jordan, Zoubin Ghahramani, Tommi S. Jaakkola and Lawrence K. Saul - 1999 |
| Inventing Discovery Tools: Combining Information Visualization with Data Mining - Ben Shneiderman - 2001 |
| An Inverse Limit of Context-Free Grammars - A New Approach to Identifiability in the Limit - Pavel Martinek - 2000 |
| Investigating the distribution assumptions in the PAC learning model - P. L. Bartlett and R. C. Williamson - 1991 |
| Investigating the value of a good input representation - Mark W. Craven and Jude W. Shavlik - 1995 |
| Investigation and Reduction of Discretization Variance in Decision Tree Induction - Pierre Geurts and Louis Wehenkel - 2000 |
| An investigation of transformation-based learning in discourse - Ken Samuel, Sandra Carberry and K. Vijay-Shanker - 1998 |
| Investigations on Measure-one Identification of Classes of Languages - Franco Montagna - 1998 |
| Irrelevant features and the subset selection problem - George H. John, Ron Kohavi and Karl Pfleger - 1994 |
| Is the pocket algorithm optimal? - Marco Muselli - 1995 |
| Iterated Phantom Induction: A Knowledge-Based Approach to Learning Control - Mark Brodie and Gerald DeJong - 2001 |
| Iterated Transductions and Efficient Learning from Positive Data: A Unifying View - Satoshi Kobayashi - 2000 |
| An Iterative and Bottom-up Procedure for Proving-by-Example - Masami Hagiya - 1993 |
| Iterative Double Clustering for Unsupervised and Semi-supervised Learning - Ran El-Yaniv and Oren Souroujon - 2001 |
| Iterative weighted least squares algorithms for neural networks classifiers - Takio Kurita - 1993 |
| varepsilon-approximations of k-label spaces - Susumu Hasegawa, Hiroshi Imai and Masaki Ishiguro - 1995 |
