 | GA-based learning of context-free grammars using tabular representations - Yasubumi Sakakibara and Mitsuhiro Kondo - 1999 |
| Gaining degrees of freedom in subsymbolic learning - B. Apolloni and D. Malchiodi - 2001 |
| Gambling in a rigged casino: the adversarial multi-armed bandit problem - Peter Auer, Nicolò Cesa-Bianchi, Yoav Freund and Robert E. Schapire - 1995 |
| A game of prediction with expert advice - V. Vovk - 1998 |
| A game of prediction with expert advice - V. G. Vovk - 1995 |
| Game theory, on-line prediction and boosting - Yoav Freund and Robert E. Schapire - 1996 |
| General and Efficient Multisplitting of Numerical Attributes - Tapio Elomaa and Juho Rousu - 1999 |
| General Bounds for Predictive Errors in Supervised Learning - Manfred Opper and David Haussler - 1995 |
| General bounds on statistical query learning and PAC learning with noise via hypothesis boosting - Javed A. Aslam and Scott E. Decatur - 1993 |
| General bounds on the mutual information between a parameter and n conditionally independent observations - David Haussler and Manfred Opper - 1995 |
| General bounds on the number of examples needed for learning probabilistic concepts - Hans Ulrich Simon - 1996 |
| General Convergence Results for Linear Discriminant Updates - Adam J. Grove, Nick Littlestone and Dale Schuurmans - 2001 |
| General Convergence Results for Linear Discriminant Updates - Adam J. Grove, Nick Littlestone and Dale Schuurmans - 1997 |
| A General Dimension for Approximately Learning Boolean Functions - Johannes Köbler and Wolfgang Lindner - 2002 |
| A General Dimension for Exact Learning - José L. Balcáazar, Jorge Castro and David Guijarro - 2001 |
| A General Framework for Induction and a Study of Selective Induction - Larry Rendell - 1986 |
| A General Framework for Parallel Distributed Processing - D. E. Rumelhart, G. E. Hinton and J. L. McClelland - 1986 |
| A General Incremental Algorithm that Infers Theory from Facts - E. Shapiro - 1981 |
| General Inductive Inference Types Based on Linearly-Ordered Sets - Andris Ambainis, Rīsiņs Freivalds and Carl H. Smith - 1996 |
| Generalisation Error Bounds for Sparse Linear Classifiers - Thore Graepel, Ralf Herbrich and John Shawe-Taylor - 2000 |
| Generalization and specialization strategies for learning r.e. languages - Sanjay Jain and Arun Sharma - 1998 |
| Generalization as search - T. M. Mitchell - 1982 |
| Generalization Bounds for Decision Trees - Yishay Mansour and David McAllester - 2000 |
| Generalization Error of Linear Neural Networks in Unidentifiable Cases - Kenji Fukumizu - 1999 |
| Generalization in partially connected layered neural networks - K. H. Kwon, K. Kang and J. H. Oh - 1994 |
| Generalization of Clauses Relative to a Theory - Peter Idestam-Almquist - 1997 |
| A generalization of Sauer's Lemma - D. Haussler and P. Long - 1995 |
| Generalization of the PAC-model for learning with partial information - Joel Ratsaby and Vitaly Maiorov - 1997 |
| Generalizations in Typed Equational Programming and Their Application to Learning Functions - A. Ishino and A. Yamamoto - 1997 |
| Generalization under Implication by using Or-Introduction - Peter Idestam-Almquist - 1993 |
| Generalization versus classification - R. Wiehagen and C. H. Smith - 1992 |
| Generalized Average-Case Analyses of the Nearest Neighbor Algorithm - Seishi Okamoto and Nobuhiro Yugami - 2000 |
| A Generalized Kalman Filter for Fixed Point Approximation and Efficient Temporal-Difference Learning - David Choi and Benjamin Van Roy - 2001 |
| Generalized Notions of Mind Change Complexity - Arun Sharma, Frank Stephan and Yuri Ventsov - 1997 |
| A generalized reinforcement-learning model: Convergence and applications - Michael L. Littman and Csaba Szepesvári - 1996 |
| A Generalized Representer Theorem - Bernhard Schölkopf, Ralf Herbrich and Alex J. Smola - 2001 |
| Generalized stochastic complexity and its applications to learning - Kenji Yamanishi - 1994 |
| Generalized teaching dimensions and the query complexity of learning - Tibor Hegedüs - 1995 |
| Generalized Unification as Background Knowledge in Learning Logic Programs - Akihiro Yamamoto - 1993 |
| Generalizing the PAC Model for Neural Net and Other Learning Applications - D. Haussler - September 1989 |
| Generalizing the PAC model: sample size bounds from metric dimension-based uniform convergence results - D. Haussler - 1989 |
| Generalizing version spaces - Haym Hirsh - 1994 |
| General Linear Relations among Different Types of Predictive Complexity - Yuri Kalnishkan - 1999 |
| General Loss Bounds for Universal Sequence Prediction - Marcus Hutter - 2001 |
| A general lower bound on the number of examples needed for learning - A. Ehrenfeucht, D. Haussler, M. Kearns and L. Valiant - 1989 |
| A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering - Pedro Domingos and Geoff Hulten - 2001 |
| A General Selection Criterion for Inductive Inference - M. P. Georgeff and C. S. Wallace - 1984 |
| A General Theory of Discrimination Learning - P. Langley - 1986 |
| The generate, test, and explain discovery system architecture - Michael de la Maza - 1994 |
| Generating accurate rule sets without global optimization - Eibe Frank and Ian H. Witten - 1998 |
| Generating all Maximal Independent Sets of Bounded-degree Hypergraphs - Nina Mishra and Leonard Pitt - 1997 |
| Gene Selection for Cancer Classification using Support Vector Machines - Isabelle Guyon, Jason Weston, Stephen Barnhill and Vladimir Vapnik - 2002 |
| Genetic AI-Translating Piaget into Lisp - G. L. Drescher - February 1986 |
| Genetic Algorithms and Machine Learning - D. E. Goldberg and J. H. Holland - 1988 |
| Genetic algorithms and machine learning - J. Grefenstette - 1993 |
| Genetic Algorithms for Protein Tertiary Structure Prediction - Steffen Schulze-Kreme - 1993 |
| Genetic Algorithms in Noisy Environments - J. Michael Fitzpatrick and John J. Grefenstette - 1988 |
| Genetic Algorithms in Search, Optimization, and Machine Learning - D. E. Goldberg - 1989 |
| Genetic Algorithms, Operators, and DNA Fragment Assembly - Rebecca J. Parsons, Stephanie Forrest and Christian Burks - 1995 |
| Genetic fitness optimization using rapidly mixing Markov chains - Paul Vitányi - 1996 |
| Genetic programming and deductive-inductive learning: a multi-strategy approach - Ricardo Aler, Daniel Borrajo and Pedro Isasi - 1998 |
| Genetic Reinforcement Learning for Neurocontrol Problems - D. Whitley, S. Dominic, R. Das and C. W. Anderson - 1993 |
| Geometrical and Statistical Properties of Systems of Linear Inequalities with Applications in Pattern Recognition - T. M. Cover - 1965 |
| Geometrical concept learning and convex polytopes - T. Hegedüs - 1994 |
| A Geometric Approach to Leveraging Weak Learners - Nigel Duffy and David P. Helmbold - 1999 |
| A geometric approach to leveraging weak learners - Nigel Duffy and David Helmbold - 2002 |
| A geometric approach to threshold circuit complexity - V. Roychowdhury, K. Siu, A. Orlitsky and T. Kailath - 1991 |
| Geometric Bounds for Generalization in Boosting - Shie Mannor and Ron Meir - 2001 |
| Geometric Methods in the Analysis of Glivenko-Cantelli Classes - Shahar Mendelson - 2001 |
| Geometric Parameters of Kernel Machines - Shahar Mendelson - 2002 |
| Geometric Properties of Naive Bayes in Nominal Domains - Huajie Zhang and Charles X. Ling - 2001 |
| Getting Order Independence in Incremental Learning - Antoine Cornuéjols - 1993 |
| Getting the most from flawed theories - Moshe Koppel, Alberto Maria Segre and Ronen Feldman - 1994 |
| A Good Oracle Is Hard to Beat - Douglas A. Cenzer and William R. Moser - 1998 |
| Graded State Machines: The Representation of Temporal Contingencies in Simple Recurrent Networks - David Servan-Schreiber, Axel Cleeremans and James L. Mcclelland - 1991 |
| Grammar enumeration and inference - R. M. Wharton - 1977 |
| Grammar Model and Grammar Induction in the System NL PAGE - Vlado Kešelj - 1998 |
| Grammatical complexity and inference - J. A. Feldman and S. Reder - 1969 |
| Grammatical inference by hill-climbing - C. M. Cook, A. Rosenfeld and A. R. Aronson - 1976 |
| Grammatical inference for even linear languages based on control sets - Yuji Takada - 1988 |
| Grammatical inference in document recognition - Alexander S. Saidi and Souad Tayeb-bey - 1998 |
| Grammatical Inference: Introduction and Survey - Part 1 - K. Fu and T. L. Booth - January 1975 |
| Grammatical Inference: Introduction and Survey - Part 2 - K. Fu and T. L. Booth - July 1975 |
| Grammatical inference using tabu search - Jean-Yves Giordano - 1996 |
| Graph learning with a nearest neighbor approach - Sven Koenig and Yury Smirnov - 1996 |
| GRAPHOIDS: A Graph-Based Logic for Reasoning about Relevance Relations, or When would x tell you more about y if you already know z - J. Pearl and A. Paz - December 1985 |
| Greedy attribute selection - Rich Caruana and Dayne Freitag - 1994 |
| A greedy method for learning mu-DNF functions under the uniforn distribution - G. Pagallo and D. Haussler - 1989 |
| Guest Editorial - Katharina Morik, Francesco Bergadano and Wray Buntine - 1994 |
| Guest editor's foreword - Robert E. Schapire - 1998 |
| Guest Editors' Introduction - Philip K. Chan, Salvatore J. Stolfo and David Wolpert - 1999 |
| Guest Editor's Introduction - Lisa Hellerstein - 1994 |
| Guest Editor's Introduction - Sally A. Goldman - 1995 |
| Guest Editors' Introduction - Stephen Muggleton and David Page - 1997 |
| Guest Editor's Introduction - Jyrki Kivinen - 2002 |
| Guest Editor's Introduction - Philip M. Long - 1997 |
| Guest Editor's Introduction - Michael J. Pazzani - 1994 |
| Guest Editors' Introduction - Yoram Singer - 2001 |
| Guest Editor's Introduction - Thomas Hancock - 1996 |
| Guest Editors' Introduction - Jonathan Baxter and Nicolò Cesa-Bianchi - 1999 |
| Guest Editors' Introduction: Machine Learning and Natural Language - Claire Cardie and Raymond J. Mooney - 1999 |
| Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination - Yoshua Bengio and Dale Schuurmans - 2002 |
| A Guided Tour Across the Boundaries of Learning Recursive Languages - T. Zeugmann and S. Lange - 1995 |
| A guided tour of Chernov bounds - T. Hagerup and C. Rub - 1990 |
| A Guided Tour of Finite Mixture Models: from Pearson to the Web - Padhraic Smyth - 2001 |
