 | 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 - S. Bai - 1994 |
| Can complexity theory benefit from learning theory? Extended Abstract - T. Hegedűs - 1993 |
| Can finite samples detect singularities of real-valued functions? - S. Ben-David - 1992 |
| 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 |
| Can PAC Learning Algorithms Tolerate Random Attribute Noise? - S. A. Goldman and R. H. Sloan - 1995 |
| The canonical distortion measure for vector quantization and function approximation - Jonathan Baxter - 1997 |
| 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 |
| The Cascade-Correlation Learning Architecture - S. E. Fahlman and C. Lebiere - 1990 |
| Case based learning in inductive inference - K. P. Jantke - 1992 |
| A case study of explanation-based control - Gerald DeJong - 1995 |
| Case-based acquisition of place knowledge - Pat Langley and Karl Pfleger - 1995 |
| Case-based learning: predictive features in indexing - Colleen M. Seifert, Kristian J. Hammond, Hollyn M. Johnson, Timothy M. Converse, Thomas F. McDougal and Scott W. VanderStoep - 1994 |
| Case-Based Learning: Predictive Features in Indexing - Colleen M. Seifert et al. - 1994 |
| Case-Based Representation and Learning of Pattern Languages - K. P. Jantke and S. Lange - 1993 |
| 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 |
| The characterisation of predictive accuracy and decision combination - Kai Ming Ting - 1996 |
| Characterisitc Sets for Polynomial Grammatical Inference - Colin de la Higuear - 1997 |
| Characteristic properties of recognizable classes of recursive functions - R. Wiehagen and W. Liepe - 1976 |
| 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 - October 1992 |
| Characterization of pattern languages - Y. Mukouchi - 1992 |
| A characterization of probabilistic inference - L. Pitt - 1984 |
| A characterization of probabilistic inference Ph.D Thesis - L. Pitt - 1984 |
| Characterization problems in the theory of inductive inference - R. Wiehagen - 1978 |
| Characterizations of Class Preserving Monotonic and Dual Monotonic Language Learning - T. Zeugmann, S. Lange and S. Kapur - 1992 |
| Characterizations of learnability for classes of { 0,...,n }-valued functions - S. Ben-David, N. Cesa-Bianchi and P. M. Long - 1992 |
| Characterizations of learnability for classes of { 0,...,n }-valued functions - S. Ben-David, N. Cesa-Bianchi, D. Haussler and P. M. Long - 1992 |
| Characterizations of Learnability for Classes of {0,,n}-valued Functions - S. Ben-David, N. Cesa-Bianchi, D. Haussler and P. M. Long - 1995 |
| Characterizations of learnability for classes of {0,...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 by Standardizing Operations - S. Jain and A. Sharma - 1994 |
| Characterizing rational versus exponential learning curves - Dale Schuurmans - 1995 |
| Characterizing the generalization performance of model selection strategies - Dale Schuurmans, Lyle H. Ungar and Dean P. Foster - 1997 |
| Charakteristche eigenschaften von erkennbaren klassen rekursiver funktionen - R. Wiehagen and W. Liepe - 1976 |
| Charcterization of Language Learning from Informant under various Monotonicity Constraints - S. Lange and T. Zeugmann - 1994 |
| Chemical Discovery as Belief Revision - Donald Rose and Pat Langley - 1986 |
| Children, Adults, and Machines as Discovery Systems - David Klahr - 1994 |
| Children, adults, and machines as discovery systems, extended abstract - David Klahr - 1994 |
| Choosing a learning team: a topological approach - K. Apsitis, R. Freivalds and C. Smith - 1994 |
| Choosing a reliable hypothesis - W. Evans, S. Rajagopalan and U. Vazirani - 1993 |
| Chunking in Soar: The Anatomy of a General Learning Mechanism - John E. Laird, Paul S. Rosenbloom and Allen Newell - 1986 |
| 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 |
| CLASSIC Learning - Michael Frazier and Leonard Pitt - 1996 |
| 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 Predicates and Languages - R. Wiehagen, C. H. Smith and T. Zeugmann - 1994 |
| Classification using information - W. I. Gasarch, M. G. Pleszkoch and M. Velauthapillai - 1994 |
| Classifier Systems and the Animat Problem - Stewart W. Wilson - 1987 |
| Classifier Systems that Learn Internal World Models - Lashon B. Booker - 1988 |
| Classifying recursive predicates and languages - R. Wiehagen, C. H. Smith and T. Zeugmann - 1995 |
| Clausal Discovery - Luc De Raedt and Luc Dehaspe - 1997 |
| Closedness properties in team learning of recursive functions - Juris Smotrovs - 1997 |
| The CN2 Induction Algorithm - Peter Clark and Tim Niblett - 1989 |
| Coding Decision Trees - C. S. Wallace and J. D. Patrick - 1993 |
| Cognitive Computation Extended Abstract - Leslie G. Valiant - 1995 |
| Co-learnability and FIN-identifiability of enumerable classes of total recursive functions - R. Freivalds, D. Gobleja, M. Karpinski and C. H. Smith - 1994 |
| 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 |
| Combining Cross-Validation and Search - C. J. C. H. Watkins - May 1987 |
| Combining postulates of naturalness in inductive inference - K. Jantke and H. Beick - 1981 |
| 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 |
| Committee-based sampling for training probabilistic classifiers - Ido Dagan and Sean P. Engelson - 1995 |
| A comparative evaluation of voting and meta-learning on partitioned data - Philip K. Chan and Salvatore J. Stolfo - 1995 |
| A comparative study of inductive logic programming methods for software fault prediction - William W. Cohen and Prem Devanbu - 1997 |
| A comparative study on feature selection in text categorization - Yiming Yang and Jan O. Pedersen - 1997 |
| 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 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 |
| Comparison of Identification Criteria for Machine Inductive Inference - J. Case and C. 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 - July 1995 |
| 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 |
| 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 - R. Kamimura - 1992 |
| 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 - A. Shinohara - 1993 |
| Complexity of Connectionist Learning with Various Node Functions - J. S. Judd - July 1987 |
| 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 |
| Complexity results on learning by neural networks - J-H. Lin and J. S. Vitter - 1991 |
| Complexity-based induction - Darrell Conklin and Ian H. Witten - 1994 |
| Complexity-based induction systems: comparisons and convergence theorems - R. J. Solomonoff - 1978 |
| Composite Geometric Concepts and Polynomial Predictability - P. M. Long and M. K. Warmuth - 1993 |
| 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 |
| 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 Learning Theory - M. Anthony and N. Biggs - 1992 |
| 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 - L. Pitt and L. Valiant - 1988 |
| Computational Limits on Team Identification of Languages - S. Jain and A. Sharma - 1993 |
| A computational model of teaching - J. Jackson and A. Tomkins - 1992 |
| Computational Sample Complexity - Scott Decatur, Oded Goldreich and Dana Ron - 1997 |
| Computer Output - D. Osherson - 1985 |
| Computer Systems that Learn - S. Weiss and C. Kulikowski - 1991 |
| Computers and thought - A. L. Samuel - 1959 |
| Concept Formation During Interactive Theory Revision - Stefan Wrobel - 1994 |
| Concept learning with geometric hypotheses - David P. Dobkin and Dimitrios Gunopulos - 1995 |
| 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 |
| Confidence estimates of classification accuracy on new examples - John Shawe-Taylor - 1997 |
| Conflict Resolution as Discovery in Particle Physics - Sakir Kocabas - 1991 |
| Connectionist Modeling and Control of Finite-State Environments - J. R. Bachrach - February 1992 |
| 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 |
| 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 |
| 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 |
| Constant depth circuits, Fourier transform, and learnability - N. Linial, Y. Mansour and N. Nisan - 1989 |
| Constrained N-to-1 generalization - S. A. Vere - 1981 |
| A constraint-based induction algorithm in FOL - Michèle Sebag - 1994 |
| Constructing Decision Trees in Noisy Domains - T. Niblett - May 1987 |
| Constructing predicate mappings for goal-directed abstraction - Y. Okubo and M. Haraguchi - 1994 |
| Constructing programs from example computations - A. W. Biermann and R. Krishnaswamy - 1976 |
| Construction of natural language sentence acceptors by a supervised learning technique - D. Coulon and D. Kayser - 1979 |
| Constructive induction for recursive programs - C. R. Mofizur and M. Numao - 1994 |
| Constructive induction using fragmentary knowledge - Steve Donoho and Larry Rendell - 1996 |
| Control structures in hypothesis spaces: the influence on learning - John Case, Sanjay Jain and Mandayam Suraj - 1997 |
| Convergence of Stochastic Processes - D. Pollard - 1984 |
| The Convergence of TD $ for General $ - Peter Dayan - 1992 |
| Convergence properties of the EM approach to learning in mixture-of-experts architectures - M. I. Jordan and L. Xu - 1993 |
| 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 - K. Basye, T. Dean and J. Vitter - 1989 |
| The correct definition of finite elasticity: corrigendum to Identification of unions - T. Motoki, T. Shinohara and K. Wright - 1991 |
| 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 Learning of Classification Knowledge and Its Applications in Robotics - Ming Tan - 1993 |
| Creating a Memory of Casual Relationships - William W. Cohen - 1993 |
| Creating Advice-Taking Reinforcement Learners - Richard Maclin and Jude W. Shavlik - 1996 |
| Credit Assignment in Rule Discovery Systems Based on Genetic Algorithms - John J. Grefenstette - 1988 |
| Criteria for Polynomial Time Conceptual Clustering - L. Pitt and R. E. Reinke - 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 - D. N. Osherson and S. 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 |
| Cryptographic hardness of distribution-specific learning - M. Kharitonov - 1993 |
| 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 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 |