 | C4.5: Programs for machine learning - J. R. Quinlan - 1993 |
| Calculation of the learning curve of Bayes optimal classification algorithm for learning a perceptron with noise - M. Opper and D. Haussler - 1991 |
| A Calculus for Logical Clustering - Shuo Bai - 1994 |
| Can Complexity Theory Benefit from Learning Theory? - Tibor Hegedüs - 1993 |
| Can complexity theory benefit from learning theory? (Extended Abstract) - T. Hegedűs - 1993 |
| Can Finite Samples Detect Singularities of Real-Valued Functions? - Shai Ben-David - 1998 |
| Can Machine Learning Offer Anything to Expert Systems? - Bruce G. Buchanan - 1989 |
| Can neural networks do better than the Vapnik-Chervonenkis bounds? - G. Tesauro and D. Cohn - 1991 |
| The canonical distortion measure for vector quantization and function approximation - Jonathan Baxter - 1997 |
| Can PAC Learning Algorithms Tolerate Random Attribute Noise? - S. A. Goldman and R. H. Sloan - 1995 |
| Capabilities of fallible FINite learning - R. Daley, B. Kalyanasundaram and M. Velauthapillai - 1993 |
| Capabilities of probabilistic learners with bounded mind changes - R. Daley and B. Kalyanasundaram - 1993 |
| Capacity and Error Estimates for Boolean Classifiers with Limited Complexity - J. Pearl - October 1979 |
| Careful abstraction from instance families in memory-based language learning - Antal Van Den Bosch - 1999 |
| The Cascade-Correlation Learning Architecture - S. E. Fahlman and C. Lebiere - 1990 |
| Cascade Generalization - João Gama and Pavel Brazdil - 2000 |
| The case against accuracy estimation for comparing induction algorithms - Foster Provost, Tom Fawcett and Ron Kohavi - 1998 |
| Case-based acquisition of place knowledge - Pat Langley and Karl Pfleger - 1995 |
| Case based learning in inductive inference - K. P. Jantke - 1992 |
| Case-Based Learning: Predictive Features in Indexing - C. M. Seifert, K. J. Hammond, H. M. Johnson, T. M. Converse, T. F. Mcdoughal and S. W. Vanderstoep - 1994 |
| Case-Based Representation and Learning of Pattern Languages - Klaus P. Jantke and Steffen Lange - 1995 |
| A case study in the use of theory revision in requirements validation - T. L. McCluskey and M. M. West - 1998 |
| A case study of explanation-based control - Gerald DeJong - 1995 |
| Category, Measure, Inductive Inference: A Triality Theorem and Its Applications - Rusins Freivalds and Carl H. Smith - 2002 |
| Causal discovery via MML - Chris Wallace, Kevin B. Korb and Honghua Dai - 1996 |
| Central Limit Theorems for Empirical Measures - R. M. Dudley - 1978 |
| The challenge of revising an impure theory - Russell Greiner - 1995 |
| Challenges in machine learning for text classification - David D. Lewis - 1996 |
| Challenges of the Email Domain for Text Classification - Jake D. Brutlag and Christopher Meek - 2000 |
| The characterisation of predictive accuracy and decision combination - Kai Ming Ting - 1996 |
| Characterisitc Sets for Polynomial Grammatical Inference - Colin de la Higuera - 1997 |
| Characteristic properties of recognizable classes of recursive functions - R. Wiehagen and W. Liepe - 1976 |
| Characteristic sets for polynominal grammatical inference - Colin De La Higuera - 1996 |
| Characteristic Sets for Unions of Regular Pattern Languages and Compactness - Masako Sato, Yasuhito Mukouchi and Dao Zheng - 1998 |
| Characterization of a class of functions synthesized by a Summers-like method using a B.M.W. matching technique - J. P. Jouannaud and Y. Kodratoff - 1979 |
| Characterization of finite identification - Y. Mukouchi - 1992 |
| Characterization of language learning from informant under various monotonicity constraints - S. Lange and T. Zeugmann - 1994 |
| Characterization of pattern languages - Y. Mukouchi - 1992 |
| Characterization problems in the theory of inductive inference - R. Wiehagen - 1978 |
| Characterizations of learnability for classes of { 0,dots ,n }-valued functions - S. Ben-David, N. Cesa-Bianchi and P. M. Long - 1992 |
| Characterizations of learnability for classes of {0,dots, n}-valued functions - Shai Ben-David, Nicolò Cesa-Bianchi, David Haussler and Philip M. Long - 1995 |
| Characterizations of monotonic and dual monotonic language learning - T. Zeugmann, S. Lange and S. Kapur - 1995 |
| Characterizing language identification by standardizing operations - Sanjay Jain and Arun Sharma - 1994 |
| Characterizing Language Learning in Terms of Computable Numberings - Sanjay Jain and Arun Sharma - 1997 |
| Characterizing Model Errors and Differences - Stephen D. Bay and Michael J. Pazzani - 2000 |
| Characterizing PAC-Learnability of Semilinear Sets - Naoki Abe - 1995 |
| Characterizing Rational Versus Exponential Learning Curves - Dale Schuurmans - 1997 |
| Characterizing Sufficient Expertise for Learning System Validation - Gunter Grieser, Klaus P. Jantke and Steffen Lange - 1998 |
| Characterizing the generalization performance of model selection strategies - Dale Schuurmans, Lyle H. Ungar and Dean P. Foster - 1997 |
| Charakteristische Eigenschaften von erkennbaren Klassen rekursiver Funktionen - R. Wiehagen and W. Liepe - 1976 |
| Chemical Discovery as Belief Revision - Donald Rose and Pat Langley - 1986 |
| CHILD: a first step towards continual learning - Mark B. Ring - 1997 |
| Children, adults, and machines as discovery systems - David Klahr - 1994 |
| Choice of Basis for Laplace Approximation - David J. C. MacKay - 1998 |
| Choosing a learning team: a topological approach - K. Aps\=ıtis, R. Freivalds and C. Smith - 1994 |
| Choosing a reliable hypothesis - W. Evans, S. Rajagopalan and U. Vazirani - 1993 |
| Choosing Multiple Parameters for Support Vector Machines - Olivier Chapelle, Vladimir Vapnik, Olivier Bousquet and Sayan Mukherjee - 2002 |
| Chunking in Soar: The Anatomy of a General Learning Mechanism - John E. Laird, Paul S. Rosenbloom and Allen Newell - 1986 |
| Classes with Easily Learnable Subclasses - Sanjay Jain, Wolfram Menzel and Frank Stephan - 2002 |
| Classical Brouwer-Heyting-Kolmogorov interpretation - Masahiko Sato - 1997 |
| CLASSIC Learning - Michael Frazier and Leonard Pitt - 1996 |
| Classification Accuracy Based on Observed Margin - John Shawe-Taylor - 1998 |
| Classification and Regression Trees - L. Breiman, J. H. Friedman, R. A. Olshen and C. J. Stone - 1984 |
| Classification by feature partitioning - H. Altay Güvenir and Izzet Sirin - 1996 |
| Classification of Individuals with Complex Structure - A. F. Bowers, C. Giraud-Carrier and J. W. Lloyd - 2000 |
| Classification of Object Sequences Using Syntactical Structure - Atsuhiro Takasu - 2001 |
| Classification of Predicates and Languages - R. Wiehagen, C. H. Smith and T. Zeugmann - 1994 |
| Classification on Data with Biased Class Distribution - Slobodan Vucetic and Zoran Obradovic - 2001 |
| Classification using information - William Gasarch, Mark G. Pleszkoch, Frank Stephan and Mahendran Velauthapillai - 1998 |
| Classification Using Information - William I. Gasarch, Mark G. Pleszkoch and Mahendran Velauthapillai - 1994 |
| Classification using Phi-machines and constructive function approximation - Doina Precup and Paul E. Utgoff - 1998 |
| Classification with Intersecting Rules - Tony Lindgren and Henrik Boström - 2002 |
| Classification with Multiple Latent Variable Models using Maximum Entropy Discrimination - Machiel Westerdijk and Wim Wiegerinck - 2000 |
| Classifier Systems and the Animat Problem - Stewart W. Wilson - 1987 |
| Classifier Systems that Learn Internal World Models - Lashon B. Booker - 1988 |
| Classifying Predicates and Languages - Carl H. Smith, Rolf Wiehagen and Thomas Zeugmann - 1997 |
| Classifying recursive predicates and languages - R. Wiehagen, C. H. Smith and T. Zeugmann - 1995 |
| A Class of Asymptotically Stable Algorithms for Learning-Rate Adaptation - S. M. Rüger - 1998 |
| A class of functions synthesized from a finite number of examples and a LISP program scheme - Y. Kodratoff - 1979 |
| A class of synthesizeable LISP programs - D. R. Smith - 1977 |
| Clausal Discovery - Luc De Raedt and Luc Dehaspe - 1997 |
| Closedness properties in ex-identification - Kalvis Aps\=ıtis, Rīsiņs Freivalds, Raimonds Simanovskis and Juris Smotrovs - 2001 |
| Closedness Properties in EX-identification of Recursive Functions - K. Aps\=ıtis, R. Freivalds, R. Simanovskis and J. Smotrovs - 1998 |
| Closedness properties in team learning of recursive functions - Juris Smotrovs - 1997 |
| Clustered Partial Linear Regression - Luíz Torgo and Joaquim Pinto da Costa - 2000 |
| Clustering Continuous Time Series - Paola Sebastiani and Marco Ramoni - 2001 |
| Clustering of sequences using minimum grammar compexity criterion - Ana L. N. Fred - 1996 |
| Clustering the Users of Large Web Sites into Communities - Georgios Paliouras, Christos Papatheodorou, Vangelis Karkaletsis and Constantine D. Spyropoulos - 2000 |
| Clustering with Instance-level Constraints - Kiri Wagstaff and Claire Cardie - 2000 |
| The CN2 Induction Algorithm - Peter Clark and Tim Niblett - 1989 |
| COBBIT - A Control Procedure for COBWEB in the Presence of Concept Drift - Fredrik Kilander and Carl Gustaf Jansson - 1993 |
| Coding Decision Trees - C. S. Wallace and J. D. Patrick - 1993 |
| Coevolutionary learning: a case study - Hugues Juille and Jordan B. Pollack - 1998 |
| Co-Evolution in the Successful Learning of Backgammon Strategy - Jordan B. Pollack and Alan D. Blair - 1998 |
| A Cognitive Bias Approach to Feature Selection and Weighting for Case-Based Learners - Claire Cardie - 2000 |
| Cognitive Computation (Extended Abstract) - Leslie G. Valiant - 1995 |
| Co-learnability and FIN-identifiability of enumerable classes of total recursive functions - R. Freivalds, Dace Gobleja, Marek Karpinski and Carl H. Smith - 1994 |
| Colearning in Differential Games - John W. Sheppard - 1998 |
| Co-Learning of Recursive Languages from Positive Data - R. Freivalds and T. Zeugmann - 1996 |
| Co-learning of total recursive functions - R. Freivalds, M. Karpinski and C. H. Smith - 1994 |
| Collaborative filtering using weighted majority prediction algorithms - Atsuyoshi Nakamura and Naoki Abe - 1998 |
| Collaborative Learning for Recommender Systems - Wee Sun Lee - 2001 |
| A Column Generation Algorithm for Boosting - Kristin P. Bennett, Ayhan Demiriz and John Shawe-Taylor - 2000 |
| Combination of Estimation Algorithms and Grammatical Inference Techniques to Learn Stochastic Context-Free Grammars - Francisco Nevado, Joan-Andreu Sánchez and José -Miguel Bened\'ı - 2000 |
| Combining Cross-Validation and Search - C. J. C. H. Watkins - May 1987 |
| Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining - Heikki Mannila - 2001 |
| Combining error-driven pruning and classification for partial parsing - Claire Cardie, Scott Mardis and David Pierce - 1999 |
| Combining labeled and unlabeled data with co-training - Avrim Blum and Tom Mitchell - 1998 |
| Combining multiple learning strategies for effective cross validation - Yiming Yang, Thomas Ault and Thomas Pierce - 2000 |
| Combining Multiple Perspectives - Bikramjit Banerjee, Sandip Debnath and Sandip Sen - 2000 |
| Combining nearest neighbor classifiers through multiple feature subsets - Stephen D. Bay - 1998 |
| Combining postulates of naturalness in inductive inference - Klaus P. Jantke and Hans-Rainer Beick - 1981 |
| Combining Reinforcement Learning with a Local Control Algorithm - Jette Randløv, Andrew G. Barto and Michael T. Rosenstein - 2000 |
| Combining statistical learning with a knowledge-based approach - a case study in intensive care monitoring - Katharina Morik, Peter Brockhausen and Thorsten Joachims - 1999 |
| Combining Symbolic and Neural Learning - Jude W. Shavlik - 1994 |
| Combining symbolic and neural learning, extended abstract - Jude Shavlik - 1994 |
| Combining top-down and bottom-up techniques in inductive logic programming - John M. Zelle, Raymond J. Mooney and Joshua B. Konvisser - 1994 |
| Comments on "Co-Evolution in the Successful Learning of Backgammon Strategy" - Gerald Tesauro - 1998 |
| Committee-based sampling for training probabilistic classifiers - Ido Dagan and Sean P. Engelson - 1995 |
| Compactness and Learning of Classes of Unions of Erasing Regular Pattern Languages - Jin Uemura and Masako Sato - 2002 |
| A comparative evaluation of voting and meta-learning on partitioned data - Philip K. Chan and Salvatore J. Stolfo - 1995 |
| A Comparative Study of Cost-Sensitive Boosting Algorithms - Kai Ming Ting - 2000 |
| A comparative study of inductive logic programming methods for software fault prediction - William W. Cohen and Prem Devanbu - 1997 |
| A Comparative Study of Two Algorithms for Automata Identification - Pedro Garcia, A. Cano and José Ruiz - 2000 |
| A comparative study on feature selection in text categorization - Yiming Yang and Jan O. Pedersen - 1997 |
| Comparing Complete and Partial Classification for Identifying Latently Dissatisfied Customers - Tom Brijs, Gilbert Swinnen, Koen Vanhoof and Geert Wets - 2000 |
| Comparing connectionist and symbolic learning methods - J. R. Quinlan - 1994 |
| Comparing methods for refining certainty-factor rule-bases - J. Jeffrey Mahoney and Raymond J. Mooney - 1994 |
| Comparing several linear-threshold learning algorithms on tasks involving superfluous attributes - Nick Littlestone - 1995 |
| Comparing the Bayes and Typicalness Frameworks - Thomas Melluish, Craig Saunders, Ilia Nouretdinov and Volodya Vovk - 2001 |
| Comparing the Minimum Description Length Principle and Boosting in the Automatic Analysis of Discourse - Tadashi Nomoto and Yuji Matsumoto - 2000 |
| Comparing the Power of Probabilistic Learning and Oracle Identification under Monotonicity Constraints - Léa Meyer - 1998 |
| Comparing Various Concepts of Function Prediction, Part 1 - K. Podnieks - 1974 |
| Comparing Various Concepts of Function Prediction, Part 2 - K. Podnieks - 1975 |
| A Comparison between Squared Error and Relative Entropy Metrics Using Several Optimization Algorithms - R. L. Watrous - 1992 |
| A comparison of ID3 and backpropogation for English text-to-speech mapping - Thomas G. Dietterich, Hermann Hild and Ghulum Bakiri - 1995 |
| A comparison of identification criteria for inductive inference of recursive real-valued functions - Eiju Hirowatari and Setsuo Arikawa - 2001 |
| A Comparison of Identification Criteria for Inductive Inference of Recursive Real-Valued Functions - Eiju Hirowatari and Setsuo Arikawa - 1998 |
| Comparison of Identification Criteria for Machine Inductive Inference - John Case and Carl H. Smith - 1983 |
| A comparison of inductive algorithms for selective and non-selective Bayesian classifiers - Moninder Singh and Gregory M. Provan - 1995 |
| A comparison of new and old algorithms for a mixture estimation problem - D. Helmbold, R. E. Schapire, Y. Singer and M. K. Warmuth - 1997 |
| A Comparison of New and Old Algorithms for a Mixture Estimation Problem - David P. Helmbold, Robert E. Schapire andYoram Singer and Manfred K. Warmuth - 1997 |
| A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms - Tjen-Sien Lim, Wei-Yin Loh and Yu-Shan Shih - 2000 |
| A Comparison of Ranking Methods for Classification Algorithm Selection - Pavel Brazdil and Carlos Soares - 2000 |
| A comparison of RBF and MLP networks for classification of biomagnetic fields - Martin F. Schlang, Klaus Abraham-Fuchs, Ralph Neuneier and Johann Uebler - 1997 |
| A comparitive study of the Kohonen self-organizing map and the elastic net - Yiu-fai Wong - 1994 |
| Competition-Based Induction of Decision Models from Examples - David Perry Greene and Stephen F. Smith - 1993 |
| A competitive approach to game learning - Christopher D. Rosin and Richard K. Belew - 1996 |
| Competitive learning by entropy minimization - Ryotaro Kamimura - 1993 |
| A Complete and Tight Average-Case Analysis of Learning Monomials - Rüdiger Reischuk and Thomas Zeugmann - 1999 |
| Complete Cross-Validatin for Nearest Neighbor Classifiers - Matthew Mullin and Rahul Sukthankar - 2000 |
| Complexity Approximation Principle and Rissanen's Approach to Real-Valued Parameters - Yuri Kalnishkan - 2000 |
| Complexity-based induction - Darrell Conklin and Ian H. Witten - 1994 |
| Complexity-based induction systems: comparisons and convergence theorems - R. J. Solomonoff - 1978 |
| Complexity Dimensions and Learnability - Shan-Hwei Nienhuys-Cheng and M. Polman - 1993 |
| Complexity in the Case Against Accuracy: When Building One Function-Free Horn Clause is as Hard as Any - Richard Nock - 1999 |
| Complexity Issues for Vacillatory Function Identification - J. Case, S. Jain and A. Sharma - 1995 |
| Complexity issues in learning by neural nets - J. Lin and J. S. Vitter - 1989 |
| Complexity of Automaton Identification from Given Data - E. M. Gold - 1978 |
| Complexity of computing Vapnik-Chervonenkis dimension and some generalized dimensions - Ayumi Shinohara - 1995 |
| Complexity of Connectionist Learning with Various Node Functions - J. S. Judd - July 1987 |
| The Complexity of Densest Region Detection - Shai Ben-David, Nadav Eiron and Hans Ulrich Simon - 2000 |
| The complexity of exactly learning algebraic concepts - V. Arvind and N. V. Vinodchandran - 1996 |
| The Complexity of Learning According to Two Models of a Drifting Environment - Philip M. Long - 1999 |
| The Complexity of Learning Concept Classes with Polynomial General Dimension - Johannes Köbler and Wolfgang Lindner - 2002 |
| Complexity of learning in artificial neural networks - Andreas Engel - 2001 |
| The Complexity of Learning Minor Closed Graph Classes - Carlos Domingo and John Shawe-Taylor - 1995 |
| Complexity of mechanized hypothesis formation - P. Pudlak and F. N. Springsteel - 1979 |
| Complexity of network training for classes of neural networks - Charles C. Pinter - 1995 |
| The Complexity of Theory Revision - Russell Greiner - 1995 |
| The complexity of universal text-learners - F. Stephan and S. A. Terwijn - 1999 |
| Complexity results on learning by neural networks - J-H. Lin and J. S. Vitter - 1991 |
| Composite Geometric Concepts and Polynomial Predictability - P. M. Long and M. K. Warmuth - 1994 |
| Composite Kernels for Hypertext Categorisation - Thorsten Joachims, Nello Cristianini and John Shawe-Taylor - 2001 |
| Comprehensible Interpretation of Relief's Estimates - Marko Robnik-ťikonja and Igor Kononenko - 2001 |
| Comprehension Grammars Generated from Machine Learning of Natural Languages - Patrick Suppes, Michael Böttner and Lin Liang - 1995 |
| Compression-based discretization of continuous attributes - Bernhard Pfahringer - 1995 |
| Computable Shell Decomposition Bounds - John Langford and David McAllester - 2000 |
| Computational Analysis of Plasma Waves and Particles in the Auroral Region Observed by Scientific Satellite - Yoshiya Kasahara, Ryotaro Niitsu and Toru Sato - 2001 |
| Computational Aspects of Parallel Attribute-Efficient Learning - Peter Damaschke - 1998 |
| Computational complexity of learning read-once formulas over different bases - L. Hellerstein and M. Karpinski - 1991 |
| The Computational Complexity of Machine Learning - M. Kearns - May 1989 |
| Computational Complexity of Problems on Probabilistic Grammars and Transducers - F. Casacuberta and Colin De La Higuera - 2000 |
| Computational Learning of Languages - Shyam Kapur - 1991 |
| Computational Learning Theory - M. Anthony and N. Biggs - 1992 |
| Computational Learning Theory, 4th European Conference, EuroCOLT '99, Nordkirchen, Germany, March 29-31, 1999, Proceedings - Paul Fischer and Hans-Ulrich Simon - March 1999 |
| Computational Learning Theory: New Models and Algorithms - R. H. Sloan - 1989 |
| Computational learning theory: survey and selected bibliography - D. Angluin - 1992 |
| Computational limitations on learning from examples - Leonard Pitt and Leslie G. Valiant - 1988 |
| Computational Limits on Team Identification of Languages - Sanjay Jain and Arun Sharma - 1996 |
| Computational Limits on Team Identification of Languages - S. Jain and A. Sharma - 1993 |
| The Computational Limits to the Cognitive Power of the Neuroidal Tabula Rasa - Jiri Wiedermann - 1999 |
| Computationally Efficient Transductive Machines - Craig Saunders, Alexander Gammerman and Volodya Vovk - 2000 |
| A Computational Model for Children's Language Acquisition Using Inductive Logic Programming - Ikuo Kobayashi, Koichi Furukawa, Tomonobu Ozaki and Mutsumi Imai - 2001 |
| A computational model of teaching - J. Jackson and A. Tomkins - 1992 |
| Computational Sample Complexity - Scott E. Decatur, Oded Goldreich and Dana Ron - 1999 |
| Computational Sample Complexity and Attribute-Efficient Learning - Rocco A. Servedio - 2000 |
| Computation of Substring Probabilities in Stochastic Grammars - Ana L. N. Fred - 2000 |
| Computer Output - D. Osherson - 1985 |
| Computers and thought - A. L. Samuel - 1959 |
| Computer Systems that Learn - S. Weiss and C. Kulikowski - 1991 |
| Computing Optimal Hypotheses Efficiently for Boosting - Shinichi Morishita - 2001 |
| Computing the maximum bichromatic discrepancy, with applications to computer graphics and machine learning - David P. Dobkin and Dimitrios Gunopulos - 1996 |
| Concept Decompositions for Large Sparse Text Data Using Clustering - Inderjit S. Dhillon and Dharmendra S. Modha - 2001 |
| Concept Formation During Interactive Theory Revision - Stefan Wrobel - 1994 |
| Concept Learning and Feature Selection Based on Square-Error Clustering - Boris Mirkin - 1999 |
| Concept learning with geometric hypotheses - David P. Dobkin and Dimitrios Gunopulos - 1995 |
| Concepts Learning with Fuzzy Clustering and Relevance Feedback - Bir Bhanu and Anlei Dong - 2001 |
| Conceptual Classifications Guided by a Concept Hierarchy - Yuhsuke Itoh and Makoto Haraguchi - 2000 |
| Conceptual Clustering, Categorization, and Polymorphy - Stephen José Hanson and Malcolm Bauer - 1989 |
| Concerning synthesis and prediction of functions - J. M. Barzdin, E. B. Kinber and K. M. Podnieks - 1974 |
| Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data - John Lafferty, Andrew McCallum and Fernando Pereira - 2001 |
| Confidence estimates of classification accuracy on new examples - John Shawe-Taylor - 1997 |
| Confirmation-Guided Discovery of First-Order Rules with Tertius - Peter A. Flach and Nicolas Lachiche - 2001 |
| Conflict Resolution as Discovery in Particle Physics - Sakir Kocabas - 1991 |
| Conjectural Equilibrium in Multiagent Learning - Michael P. Wellman and Junling Hu - 1998 |
| Connectionist Modeling and Control of Finite-State Environments - J. R. Bachrach - February 1992 |
| A connectionist model of the learning of personal pronouns in English - Thomas R. Shultz, David Buckingham and Yuriko Oshima-Takane - 1994 |
| Connectionist Nonparametric Regression: Multilayer Feedforward Networks can Learn Arbitrary Mappings - H. White - 1990 |
| Connections between Identifying Functionals, Standardizing Operations, and Computable Numberings - R. Freivalds, E. B. Kinber and R. Wiehagen - 1984 |
| CONSENSUS: A Statistical Learning Procedure in a Connectionist Network - G. J. Goetsch - May 1986 |
| Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction - Branko Kavsek, Nada Lavrac and Anuska Ferligoj - 2001 |
| A conservation law for generalization performance - Cullen Shaffer - 1994 |
| Conservativeness and monotonicity for learning algorithms - E. Takimoto and A. Maruoka - 1993 |
| Consideration of risk in reinforcement learning - Matthias Heger - 1994 |
| The Consistency Dimension and Distribution-Dependendent Learning from Queries - José L. Balcázar, Jorge Castro, David Guijarro and Hans-Ulrich Simon - 2002 |
| The Consistency Dimension and Distribution-Dependent Learning from Queries - Jose L. Balcazar, Jorge Castro, David Guijarro and Hans-Ulrich Simon - 1999 |
| The Consistency of Greedy Algorithms for Classification - Shie Mannor, Ron Meir and Tong Zhang - 2002 |
| Consistency Queries in Information Extraction - Gunter Grieser, Klaus P. Jantke and Steffen Lange - 2002 |
| Consistent Inference of Probabilities for Reproducible Experiments - Y. Tikochinsky, N. Z. Tishby and R. D. Levine - 1984 |
| Consistent inference of probabilities in layered networks: predictions and generalizations - N. Tishby, E. Levin and S. Solla - 1989 |
| Consistent Polynomial Identification in the Limit - Werner Stein - 1998 |
| A Consistent Strategy for Boosting Algorithms - Gábor Lugosi and Nicolas Vayatis - 2002 |
| Constant depth circuits, Fourier transform, and learnability - N. Linial, Y. Mansour and N. Nisan - 1989 |
| A Constant-Factor Approximation Algorithm for the k-Median Problem (Extended Abstract) - Moses Charikar, Sudipto Guha, Eva Tardos and David B. Shmoys - 1999 |
| Constrained K-means Clustering with Background Knowledge - Kiri Wagstaff, Claire Cardie, Seth Rogers and Stefan Schroedl - 2001 |
| Constrained N-to-1 generalization - S. A. Vere - 1981 |
| A constraint-based induction algorithm in FOL - Michèle Sebag - 1994 |
| Constraint Classification: A New Approach to Multiclass Classification - Sariel Har-Peled, Dan Roth and Dav Zimak - 2002 |
| Constructing a Critical Casebase to Represent a Lattice-Based Relation - Ken Satoh - 2001 |
| Constructing Decision Trees in Noisy Domains - T. Niblett - May 1987 |
| Constructing Inductive Applications by Meta-Learning with Method Repositories - Hidenao Abe and Takahira Yamaguchi - 2001 |
| Constructing predicate mappings for goal-dependent abstraction - Yoshiaki Okubo and Makoto Haraguchi - 1998 |
| Constructing programs from example computations - A. W. Biermann and R. Krishnaswamy - 1976 |
| Constructing X-of-N Attributes for Decision Tree Learning - Zijian Zheng - 2000 |
| Construction of natural language sentence acceptors by a supervised learning technique - D. Coulon and D. Kayser - 1979 |
| Constructive Feature Learning and the Development of Visual Expertise - Justus H. Piater and Roderic A. Grupen - 2000 |
| Constructive Induction for Recursive Programs - Chowdhury Rahman Mofizur and Masayuki Numao - 1994 |
| Constructive induction using fragmentary knowledge - Steve Donoho and Larry Rendell - 1996 |
| Constructive Learning of Context-Free Languages with a Subpansive Tree - Noriko Sugimoto, Takashi Toyoshima, Shinichi Shimozono and Kouichi Hirata - 2000 |
| Constructive learning of translations based on dictionaries - Noriko Sugimoto, Kouichi Hirata and Hiroki Ishizaka - 1996 |
| Content-Based Similarity Assessment in Multi-segmented Medical Image Data Bases - George Potamias - 2001 |
| Continuous-Action Q-Learning - José del R. Millán, Daniele Posenato and Eric Dedieu - 2002 |
| Continuous Drifting Games - Yoav Freund and Manfred Opper - 2000 |
| Continuous-Time Hierarchial Reinforcement Learning - Mohammad Ghavamzadeh and Sridhar Mahadevan - 2001 |
| Contrastive learning with graded random networks - Javier R. Movellan and James L. McClelland - 1994 |
| Controlled Redundancy in Incremental Rule Learning - L. Torgo - 1993 |
| Control structures in hypothesis spaces: the influence on learning - John Case, Sanjay Jain and Mandayam Suraj - 2002 |
| Control structures in hypothesis spaces: the influence on learning - John Case, Sanjay Jain and Mandayam Suraj - 1997 |
| Convergence analysis of temporal-difference learning algorithms with linear function approximation - Vladislav Tadić - 1999 |
| Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences - Marcus Hutter - 2001 |
| Convergence of a Generalized SMO Algorithm for SVM Classifier Design - S. S. Keerthi and E. G. Gilbert - 2002 |
| Convergence of Gradient Dynamics with a Variable Learning Rate - Michael Bowling and Manuela Veloso - 2001 |
| Convergence of Stochastic Processes - D. Pollard - 1984 |
| The Convergence of TD(lambda) for General lambda - Peter Dayan - 1992 |
| Convergence Problems of General-Sum Multiagent Reinforcement Learning - Michael Bowling - 2000 |
| Convergence Rate of Minimization Learning for Neural Networks - M. H. Mohamed, T. Minamoto and K. Niijima - 1998 |
| Convergence Rates of the Voting Gibbs Classifier, with Application to Bayesian Feature Selection - Andrew Y. Ng and Michael I. Jordan - 2001 |
| Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms - Satinder Singh, Tommi Jaakkola, Michael L. Littman and Csaba Szepesvári - 2000 |
| Convergence results for the EM approach to Mixtures of Experts Architectures - M. I. Jordan and L. Xu - 1995 |
| Convergence Results in the Hopfield Model - J. Kómlos and R. Paturi - September 1987 |
| Convergence to Nearly Minimal Size Grammars by Vacillating Learning Machines - J. Case, S. Jain and A. Sharma - 1990 |
| Convergence to nearly minimal size grammars by vacillating learning machines - S. Jain, A. Sharma and J. Case - 1989 |
| A convergent reinforcement learning algorithm in the continuous case: the finite-element reinforcement learning - Rémi Munos - 1996 |
| CONVINCE: A Conversational Inference Consolidation Engine - J. H. Kim - 1983 |
| Coping with uncertainty in map learning - Kenneth Basye, Thomas Dean and Jeffrey Scott Vitter - 1997 |
| The correct definition of finite elasticity: corrigendum to Identification of unions - T. Motoki, T. Shinohara and K. Wright - 1991 |
| Correcting noisy data - Choh Man Teng - 1999 |
| Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning - Mark A. Hall - 2000 |
| Corrigendum for: Learnability of description logics - William W. Cohen and Haym Hirsh - 1995 |
| Corrigendum to Types of noise in data for concept learning - R. H. Sloan - 1992 |
| Cost-sensitive feature reduction applied to a hybrid genetic algorithm - Nada Lavrač, Dragan Gamberger and Peter Turney - 1996 |
| Cost-Sensitive Learning of Classification Knowledge and Its Applications in Robotics - Ming Tan - 1993 |
| Costs of general purpose learning - John Case, Keh-Jiann Chen and Sanjay Jain - 2001 |
| Costs of General Purpose Learning - John Case, Keh-Jiann Chen and Sanjay Jain - 1999 |
| Counting Extensional Differences in BC-Learning - Frank Stephan and Sebastiaan A. Terwijn - 2000 |
| Coupled Clustering: a Method for Detecting Structural Correspondence - Zvika Marx, Ido Dagan and Joachim Buhmann - 2001 |
| Covering cubes by random half cubes, with applications to binary neural networks - Jeong Han Kim and James R. Roche - 1998 |
| Covering numbers for support vector machines - Ying Guo, Peter L. Bartlett, John Shawe-Taylor and Robert C. Williamson - 1999 |
| Crafting Papers on Machine Learning - Pat Langley - 2000 |
| Creating Advice-Taking Reinforcement Learners - Richard Maclin and Jude W. Shavlik - 1996 |
| Creating a Memory of Casual Relationships - William W. Cohen - 1993 |
| Credit Assignment in Rule Discovery Systems Based on Genetic Algorithms - John J. Grefenstette - 1988 |
| Criteria for Polynomial-Time (Conceptual) Clustering - Leonard Pitt and Robert E. Reinke - 1988 |
| Criteria for specifying machine complexity in learning - Changfeng Wang and Santosh S. Venkatesh - 1995 |
| Criteria of Language Learning - Daniel N. Osherson and Scott Weinstein - 1982 |
| A Critical Look at Experimental Evaluations of EBL - Alberto Segre, Charles Elkan and Alexander Russell - 1991 |
| Critical Points for Least-Squares Problems Involving Certain Analytic Functions, with Applications to Sigmoidal Nets - Eduardo D. Sontag - 1995 |
| A critical survey of rule learning programs - A. Bundy and B. Silver - 1981 |
| A Critique of the Valiant Model - W. Buntine - 1989 |
| Cross-validation and modal theories - Timothy L. Bailey and Charles Elkan - 1995 |
| Cross-validation for binary classification by real-valued functions: theoretical analysis - Martin Anthony and Sean B. Holden - 1998 |
| Cryptographic hardness of distribution-specific learning - M. Kharitonov - 1993 |
| Cryptographic limitations on learning Boolean formulae and finite automata - Michael Kearns and Leslie Valiant - 1994 |
| Cryptographic limitations on learning Boolean formulae and finite automata - M. Kearns and L. G. Valiant - 1989 |
| Cryptographic Limitations on Learning One-Clause Logic Programs - William Cohen - 1993 |
| Cryptographic limitations on parallelizing membership and equivalence queries with applications to random-self-reductions - Marc Fischlin - 2001 |
| Cryptographic Limitations on Parallelizing Membership and Equivalence Queries with Applications to Random Self-Reductions - Marc Fischlin - 1998 |
| Cryptographic lower bounds for learnability of Boolean functions on the uniform distribution - Michael Kharitonov - 1995 |
| Cryptographic lower bounds on learnability of Boolean functions on the uniform distribution - M. Kharitonov - 1992 |
| CSM: A Computational Model of Cumulative Learning - Hayong Harry Zhou - 1990 |
