 | 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. G. Vovk - 1995 |
| Game theory, on-line prediction and boosting - Yoav Freund and Robert E. Schapire - 1996 |
| 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 - 1997 |
| 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 |
| A General Lower Bound on the Number of Examples Needed for Learning - A. Ehrenfeucht and D. Haussler - September 1989 |
| A general lower bound on the number of examples needed for learning - A. Ehrenfeucht, D. Haussler, M. Kearns and L. G. Valiant - 1989 |
| A General Selection Criterion for Inductive Inference - M. P. Georgeff and C. S. Wallace - 1984 |
| A General Theory of Discrimination Learning - P. Langley - 1986 |
| Generalization as search - T. M. Mitchell - 1982 |
| 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 |
| Generalization versus classification - R. Wiehagen and C. H. Smith - 1992 |
| 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 |
| Generalized teaching dimensions and the query complexity of learning - Tibor Hegedüs - 1995 |
| Generalized unification as background knowledge in learning logic programs - A. 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 |
| The generate, test, and explain discovery system architecture - Michael de la Maza - 1994 |
| Generating all Maximal Independent Sets of Bounded-degree Hypergraphs - Nina Mishra and Leonard Pitt - 1997 |
| Genetic AI-Translating Piaget into Lisp - G. L. Drescher - February 1986 |
| Genetic algorithms and machine learning - J. Grefenstette - 1993 |
| Genetic Algorithms and Machine Learning - D. E. Goldberg and J. H. Holland - 1988 |
| 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 Reinforcement Learning for Neurocontrol Problems - Darrell Whitley et al. - 1993 |
| A geometric approach to threshold circuit complexity - V. Roychowdhury, K. Siu, A. Orlitsky and T. Kailath - 1991 |
| 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 |
| Getting the most from flawed theories - Moshe Koppel, Alberto Maria Segre and Ronen Feldman - 1994 |
| 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 |
| Grammatical complexity and inference - J. A. G. J. H. J. J. Feldman and S. Reder - 1969 |
| Grammatical inference: an old and new paradigm - Yasubumi Sakakibara - 1995 |
| Grammatical inference by hill-climbing - C. M. Cook, A. Rosenfeld and A. R. Aronson - 1976 |
| 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 |
| 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 -DNF functions under the uniforn distribution - G. Pagallo and D. Haussler - 1989 |
| Guest Editorial - Katharina Morik, Francesco Bergadano and Wray Buntine - 1994 |
| Guest Editors’ Introduction - Stephen Muggleton and David Page - 1997 |
| Guest Editor’s Introduction - Philip M. Long - 1997 |
| Guest Editor’s Introduction - Michael J. Pazzani - 1994 |
| Guest Editor’s Introduction - Sally A. Goldman - 1995 |
| Guest Editor’s Introduction by Lisa Hellerstein - Lisa Hellerstein - 1994 |
| Guest Editor’s Introduction by Thomas Hancock - Thomas Hancock - 1996 |
| 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 |