| **Rademacher and Gaussian Complexities: Risk Bounds and Structural Results** - *Peter L. Bartlett and Shahar Mendelson* - 2001 |

| **Radial Basis Function Neural Networks Have Superlinear VC Dimension** - *Michael Schmitt* - 2001 |

| **Radial Basis Functions for Multivariable Interpolation: A Review** - *M. J. D. Powell* - 1987 |

| **Random DFA's can be approximately learned from sparse uniform examples** - *K. J. Lang* - 1992 |

| **Random Forests** - *Leo Breiman* - 2001 |

| **A randomized ANOVA procedure for comparing performance curves** - *Justus H. Piater, Paul R. Cohen, Xiaoqin Zhang and Michael Atighetchi* - 1998 |

| **Randomized approximate aggregating strategies and their applications to prediction and discrimination** - *Kenji Yamanishi* - 1995 |

| **A randomized approximation of the MDL for stochastic models with hidden variables** - *Kenji Yamanishi* - 1996 |

| **Randomized hypotheses and minimum disagreement hypotheses for learning with noise** - *Nicolò Cesa-Bianchi, Paul Fischer, Eli Shamir and Hans Ulrich Simon* - 1997 |

| **Randomizing Outputs to Increase Prediction Accuracy** - *Leo Breiman* - 2000 |

| **Randomly Fallible Teachers: Learning Monotone DNF with an Incomplete Membership Oracle** - *Dana Angluin and Donna K. Slonim* - 1994 |

| **A random sampling based algorithm for learning the intersection of half-spaces (extended abstract)** - *Santosh Vempala* - 1997 |

| **A Random Sampling Technique for Training Support Vector Machines** - *Jose Balcàzar, Yang Dai and Osamu Watanabe* - 2001 |

| **Rapid Construction of algebraic axioms from samples** - *J. M. Barzdin and G. Barzdin* - 1991 |

| **Rate of approximation results motivated by robust neural network learning** - *C. Darken, M. Donahue, L. Gurvits and E. Sontag* - 1993 |

| **Rates of convergence for minimum contrast estimators** - *L. Birge and P. Massart* - 1993 |

| **Rates of Convergence for Variable Resolution Schemes in Optimal Control** - *Rémi Munos and Andrew W. Moore* - 2000 |

| **Rationality** - *Leslie G. Valiant* - 1995 |

| **RBF Neural Networks and Descartes' Rule of Signs** - *Michael Schmitt* - 2002 |

| **Read-thrice DNF is hard to learn with membership and equivalence queries** - *H. Aizenstein, L. Hellerstein and L. Pitt* - 1992 |

| **Read-twice DNF Formulas are Properly Learnable** - *K. Pillaipakkamnatt and V. Raghavan* - 1994 |

| **Real Analysis** - *H. Royden* - 1963 |

| **Realization of boolean functions with a small number of zeros by disjunctive normal forms, and related problems** - *Y. Zhuravlev and Y. Kogan* - 1985 |

| **Real language learning** - *Jerome A. Feldman* - 1998 |

| **Real-Valued Multiple-Instance Learning with Queries** - *Daniel R. Dooly, Sally A. Goldman and Stephen S. Kwek* - 2001 |

| **Real-World Robotics: Learning to Plan for Robust Execution** - *Scott W. Bennett and Gerald F. DeJong* - 1996 |

| **Reasoning by Analogy as a Partial Identity between Models** - *Makoto Haraguchi and Setsuo Arikawa* - 1986 |

| **Recent advances in inductive logic programming** - *S. Muggleton* - 1994 |

| **Recent Advances in Robot Learning** - *J. Franklin and T. Mitchell and S. Thrun* - 1996 |

| **Recent advances of grammatical inference** - *Yasubumi Sakakibara* - 1997 |

| **Recent Methods for RNA Modeling Using Stochastic Context-Free Grammars** - *Yasubumi Sakakibara, Michael Brown, Richard Hughey, I. Saira Mian, Kimmen Sjölander, Rebecca C. Underwood and David Haussler* - 1994 |

| **Recent Results on Boolean Concept Learning** - *M. Kearns, M. Li, L. Pitt and L. Valiant* - June 1987 |

| **Recognition and exploitation of contextual clues via incremental meta-learning** - *Gerhard Widmer* - 1996 |

| **Recognizing algorithms for recursive functions** - *R. Klette* - 1976 |

| **A Reconfigurable Analog (VLSI Neural Network Chip** - *H. P. Graf, S. Satyanarayana and Y. Tsividis* - 1989 |

| **Reconstructing algebraic functions from mixed data** - *S. Ar, R. J. Lipton, R. Rubinfeld and M. Sudan* - 1992 |

| **Recovery from multiple faults in relational theory** - *S. Tangkitvanich and M. Shimura* - 1992 |

| **Recurrent neural networks with continuous topology adaptation, Kalman filter bsed training** - *Dragan Obradovic* - 1997 |

| **Recurrent neural networks with time-dependent inputs and outputs** - *Volkmar Sterzing and Bernd Schürmann* - 1995 |

| **Recursion Theoretic Characterizations of Language Learning** - *S. Jain and A. Sharma* - 1989 |

| **Recursion theoretic models of learning: some results and intuitions** - *Carl H. Smith and William I. Gasarch* - 1995 |

| **Recursive automatic bias selection for classifier construction** - *Carla E. Brodley* - 1995 |

| **Recursiveness of the Enumerating Functions Increases the Inferrability of Recursively Enumerable Sets** - *R. Freivalds* - 1985 |

| **Reducing complexity of decision trees with two variable tests** - *R. A. Pearson and E. K. T. Smith* - 1996 |

| **Reducing misclassification costs** - *Michael Pazzani, Christopher Merz, Patrick Murphy, Kamal Ali, Timothy Hume and Clifford Brunk* - 1994 |

| **Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers** - *Erin L. Allwein, Robert E. Schapire and Yoram Singer* - 2000 |

| **Reducing Search Space in Solving Higher-Order Equations** - *Tetsuo Ida, Mircea Marin and Taro Suzuki* - 2001 |

| **Reducing the number of queries in self-directed learning** - *Yiqun L. Yin* - 1995 |

| **Reducing the small disjuncts problem by learning probabilistic concept descriptions** - *Kamal M. Ali and Michael J. Pazzani* - 1995 |

| **Reductions for learning via queries** - *William Gasarch and Geoffrey R. Hird* - 1995 |

| **Reduction Techniques for Instance-Based Learning Algorithms** - *D. Randall Wilson and Tony R. Martinez* - 2000 |

| **Redundant noisy attributes, attribute errors, and linear threshold learning using Winnow** - *N. Littlestone* - 1991 |

| **Refined Incremental Learning** - *S. Lange and T. Zeugmann* - 1995 |

| **Refined Query Inference** - *E. B. Kinber and T. Zeugmann* - 1989 |

| **Refinement of Rule Sets with JoJo** - *Dieter Fensel and Markus Wiese* - 1993 |

| **Refinements of Inductive Inference by Popperian and Reliable Machines** - *John Case, Sanjay Jain and Suzanne Ngo-Manguelle* - 1994 |

| **Refinements of inductive inference by Popperian machines** - *J. Case and S. Ngo-Manguelle* - 1979 |

| **Refining algorithms with knowledge-based neural networks: improving the Cho-Fasman algorithm for protein folding** - *Richard Maclin and Jude W. Shavlik* - 1994 |

| **Refining initial points for K-Means clustering** - *Paul S. Bradley and Usama M. Fayyad* - 1998 |

| **Refining Numerical Constants in First Order Logic Theories** - *Marco Botta and Roberto Piola* - 2000 |

| **Reflecting and Self-Confident Inductive Inference Machines** - *Klaus P. Jantke* - 1995 |

| **Reflecting inductive inference machines and its improvement by therapy** - *Gunter Grieser* - 1996 |

| **Reflective Inductive Inference of Recursive Functions** - *Gunter Grieser* - 2002 |

| **Reformulation of Explanation by Linear Logic - Toward Logic for Explanation -** - *Jun Arima and Hajime Sawamura* - 1993 |

| **Refutable/Inductive Learning from Neighbor Examples and Its Application to Decision Trees over Patterns** - *Masako Sato, Yasuhito Mukouchi and Mikiharu Terada* - 2001 |

| **Refutable inference of functions computed by loop programs** - *T. Miyahara* - 1995 |

| **Refutable Language Learning with a Neighbor System** - *Yasuhito Mukouchi and Masako Sato* - 2001 |

| **Refutably Probably Approximately Correct Learning** - *Satoshi Matsumoto and Ayumi Shinohara* - 1994 |

| **Refuting Learning Revisited** - *Wolfgang Merkle and Frank Stephan* - 2001 |

| **A region-based learning approach to discovering temporal structures in data** - *Wei Zhang* - 1999 |

| **Regression NSS: an alternative to cross validation** - *Michael P. Perrone and Brian S. Blais* - 1995 |

| **Regressiveness** - *M. Fulk* - 1989 |

| **Regret bounds for prediction problems** - *Geoffrey J. Gordon* - 1999 |

| **Regular grammatical inferencefrom positive and negative samples by genetic search: The GIG method** - *P. Dupon* - 1994 |

| **Regular inference with a tail-clustering method** - *L. Miclet* - 1980 |

| **Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks** - *T. Poggio and F. Girosi* - February 23 1990 |

| **Regularization learning of neural networks for generalization** - *Shotaro Akaho* - 1993 |

| **Regularized Principal Manifolds** - *Alex J. Smola, Robert C. Williamson, Sebastian Mika and Bernhard Schölkopf* - 1999 |

| **A Reinforcement Connectionist Approach to Robot Path Finding in Non-Maze-Like Environments** - *José Del R. Millán and Carme Torras* - 1992 |

| **A Reinforcement Learning Algorithm Applied to Simplified Two-Player Texas Hold'em Poker** - *Fredrik A. Dahl* - 2001 |

| **Reinforcement learning and mistake bounded algorithms** - *Yishay Mansour* - 1999 |

| **Reinforcement Learning Architectures for Animats** - *R. S. Sutton* - 1991 |

| **Reinforcement learning by stochastic hill climbing on discounted reward** - *Hajime Kimura, Masayuki Yamamura and Shigenobu Kobayashi* - 1995 |

| **Reinforcement Learning for Call Admission Control and Routing under Quality of Service Constraints in Multimedia Networks** - *Hui Tong and Timothy X. Brown* - 2002 |

| **Reinforcement Learning in Dynamic Environments using Instantiated Information** - *Marco A. Wiering* - 2001 |

| **Reinforcement learning in factories: the auton project (abstract)** - *Andrew W. Moore* - 1996 |

| **Reinforcement Learning in POMDP's via Direct Gradient Ascent** - *Jonathan Baxter and Peter L. Bartlett* - 2000 |

| **Reinforcement learning in POMDPs with function approximation** - *Hajime Kimura, Kazuteru Miyazaki and Shigenobu Kobayashi* - 1997 |

| **Reinforcement Learning with Bounded Risk** - *Peter Geibel* - 2001 |

| **Reinforcement Learning with Replacing Eligibility Traces** - *Satinder P Singh and Richard S. Sutton* - 1996 |

| **Reinterpreting the Category Utility Function** - *Boris Mirkin* - 2001 |

| **Rekursionstheoretische Charakterisierung von erkennbaren Klassen rekursiver Funktionen** - *R. Wiehagen and H. Jung* - 1977 |

| **Relational instance-based learning** - *Werner Emde and Dietrich Wettschereck* - 1996 |

| **Relational Instance-Based Learning with Lists and Terms** - *Tamás Horváth, Stefan Wrobel and Uta Bohnebeck* - 2001 |

| **Relational Learning with Statistical Predicate Invention: Better Models for Hypertext** - *Mark Craven and Seán Slattery* - 2001 |

| **Relational reinforcement learning** - *Sašo Džeroski, Luc De Raedt and Hendrik Blockeel* - 1998 |

| **Relational Reinforcement Learning** - *Saso Dzeroski, Luc De Raedt and Kurt Driessens* - 2001 |

| **Relations between probabilistic and team one-shot learners** - *R. Daley, L. Pitt, M. Velauthapillia and T. Will* - 1991 |

| **Relationships between PAC-learning algorithms and weak Occam algorithms** - *E. Takimoto and A. Maruoka* - 1992 |

| **Relative Expexted Instantaneous Loss Bounds** - *Jürgen Forster and Manfred Warmuth* - 2000 |

| **Relative information** - *G. Jumarie* - 1990 |

| **Relative Loss Bounds for Multidimensional Regression Problems** - *J. Kivinen and M. K. Warmuth* - 2001 |

| **Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions** - *Katy S. Azoury and M. K. Warmuth* - 2001 |

| **Relative Loss Bounds for Temporal-Difference Learning** - *Jürgen Forster and Manfred Warmuth* - 2000 |

| **Relative Sizes of Learnable Sets** - *Lance Fortnow, Rīsiņs Freivalds, William I. Gasarch, Martin Kummer, Stuart A. Kurtz, Carl H. Smith and Frank Stephan* - 1998 |

| **Relative Unsupervised Discretization for Regression Problems** - *Marcus-Christopher Ludl and Gerhard Widmer* - 2000 |

| **The Relaxed Online Maximum Margin Algorithm** - *Yi Li and Philip M. Long* - 2002 |

| **Relevance Feedback using Support Vector Machines** - *Harris Drucker, Behzad Shahrary and David C. Gibbon* - 2001 |

| **Reliable and useful learning** - *J. Kivinen* - 1989 |

| **A remark on discovery algorithms for grammars** - *E. Shamir* - 1962 |

| **Removing the genetics from the standard genetic algorithm** - *Shumeet Baluja and Rich Caruana* - 1995 |

| **Repairing Faulty Mixture Models using Density Estimation** - *Peter Sand and Andrew W. Moore* - 2001 |

| **A Reply to Cohen's Book Review of Creating a Memory of Causal Relationships** - *Michael Pazzani* - 1993 |

| **A Reply to Hellerstein's Book Review of Machine Learning: A Theoretical Approach** - *B. K. Natarajan* - 1993 |

| **A Reply to Honavar's Book Review of Neural Network Design and the Complexity of Learning** - *J. Stephen Judd* - 1992 |

| **A Reply to Pazzani's Book Review of Inductive Logic Programming: Techniques and Applications** - *Nada Lavrac and Saso Dzeroski* - 1996 |

| **A Reply to Reich's Book Review of Exemplar-Based Knowledge Acquisition** - *Ray Bareiss* - 1991 |

| **A Reply to Towell's Book Review of Neural Network Perception for Mobile Robot Guidance** - *Dean A. Pomerleau* - 1995 |

| **A Reply to Zito-Wolf's Book Review of Learning Search Control Knowledge: An Explanation-Based Approach** - *Steven Minton* - 1991 |

| **Representation changes for efficient learning in structural domains** - *Jean-Daniel Zucker and Jean-Gabriel Ganascia* - 1996 |

| **Representation of finite state automata in recurrent radial basis function networks** - *Paolo Frasconi, Marco Gori, Marco Maggini and Giovanni Soda* - 1996 |

| **The representation of recursive languages and its impact on the efficiency of learning** - *S. Lange* - 1994 |

| **Representation Propoerties of Networks: Kolmogorov's Theorm Is Irrelevant** - *T. Poggio and F. Girosi* - 1989 |

| **The Representation Race - Preprocessing for Handling Time Phenomena** - *Katharina Morik* - 2000 |

| **representing and learning quality-improving search control knowledge** - *M. Alicia Pérez* - 1996 |

| **Representing Probabilistic Rules with Networks of Gaussian Basis Functions** - *Volker Tresp, Jürgen Hollatz and Subutai Ahmad* - 1997 |

| **Requests for hints that return no hints** - *D. Angluin* - 1988 |

| **Research in the Theory of Inductive Inference by GDR mathematicians - A Survey** - *R. Klette and R. Wiehagen* - 1980 |

| **(Research Note) Classification accuracy: Machine learning vs. explicit knowledge acquisition** - *Arie Ben-David and Janice Mandel* - 1995 |

| **Research Note on Decision Lists** - *Ron Kohavi and Scott Benson* - 1993 |

| **Research Papers in Machine Learning** - *P. Langley* - 1987 |

| **Residual algorithms: reinforcement learning with function approximation** - *Leemon Baird* - 1995 |

| **Residual Q-learning applied to visual attention** - *Cesar Bandera, Francisco J. Vico, Jose M. Bravo, Mance E. Harmon and Leemon C. Baird III* - 1996 |

| **Resource-Bounded Measure and Learnability** - *W. Lindner, R. Schuler and O. Watanabe* - 2000 |

| **Resource Bounded Next Value and Explanatory Identification: Learning Automata, Patterns and Polynomials On-Line** - *Susanne Kaufmann and Frank Stephan* - 1997 |

| **Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching** - *M. Sebag and C. Rouveirol* - 2000 |

| **Restrictions on Grammar Size in Language Identification** - *S. Jain and A. Sharma* - March 1991 |

| **A result of Vapnik with applications** - *M. Anthony and J. Shawe-Taylor* - 1990 |

| **A result relating convex n-widths to covering numbers with some applications to neural networks** - *Jonathan Baxter and Peter Bartlett* - 1997 |

| **Results of the Abbadingo one DFA learning competition and a new evidence-driven state merging algorithm** - *Kevin J. Lang, Barak A. Pearlmutter and Rodney A. Price* - 1998 |

| **Results on Learnability and the Vapnik-Chervonenkis Dimension** - *N. Linial, Y. Mansour and R. L. Rivest* - January 1991 |

| **Retrofitting decision tree classifiers using kernel density estimation** - *Padhraic Smyth, Alexander Gray and Usama M. Fayyad* - 1995 |

| **Review of Five Empirical Learning Systems Within a Proposed Schemata** - *M. Gams and N. Lavrac* - May 1987 |

| **Review of Inductive Logic Programming: Techniques and Applications by Nada Lavrac, Saso Dzeroski** - *Michael Pazzani* - 1996 |

| **Review of "Limiting recursion" by E.M. Gold and "Trial and error predicates and the solution to a problem of Mostowski" by H. Putnam** - *N. Shapiro* - 1971 |

| **A Review of Machine Learning at AAAI-87** - *R. Greiner, B. Silver, S. Becker and M. Grüninger* - 1988 |

| **A Review of the Fourth International Workshop on Machine Learning** - *R. P. Hall, B. Falkenhainer, N. Flann, S. Hampson, R. Reinke, J. Shrager, M. H. Sims and P. Tadepalli* - 1987 |

| **Revision of production system rule-bases** - *Patrick M. Murphy and Michael J. Pazzani* - 1994 |

| **Reward functions for accelerated learning** - *Maja J. Mataric* - 1994 |

| **Rich Classes Inferable from Positive Data: Length-Bounded Elementary Formal Systems** - *Takeshi Shinohara* - 1994 |

| **Ridge regression learning algorithm in dual variables** - *G. Saunders, A. Gammerman and V. Vovk* - 1998 |

| **Ridge Regressioon Confidence Machine** - *Ilia Nouretdinov, Tom Melluish and Volodya Vovk* - 2001 |

| **Rigel: An Inductive Learning System** - *Roberto Gemello, Franco Mana and Lorenza Saitta* - 1991 |

| **Rigorous learning curve bounds from statistical mechanics** - *D. Haussler, M. Kearns, H. S. Seung and N. Tishby* - 1994 |

| **Risk-Sensitive Reinforcement Learning** - *Oliver Mihatsch and Ralph Neuneier* - 2002 |

| **RL-TOPs: an architecture for modularity and re-use in reinforcement learning** - *Malcolm R. K. Ryan and Mark D. Pendrith* - 1998 |

| **RNA Modeling Using Gibbs Sampling and Stochastic Context Free Grammars** - *L. Grate, M. Herbster, R. Hughey, I. S. Mian, H. Noller and D. Haussler* - August 1994 |

| **Robot Baby 2001** - *Paul R. Cohen, Tim Oates, Niall Adams and Carole R. Beal* - 2001 |

| **Robot learning from demonstration** - *Christopher G. Atkeson and Stefan Schaal* - 1997 |

| **Robot localization in a grid** - *Chinda Wongngamnit and Dana Angluin* - 2001 |

| **Robot Navigation with Distance Queries** - *Dana Angluin, Jeffery Westbrook and Wenhong Zhu* - 2000 |

| **Robot Programming by Demonstration (RPD): Supporting the Induction by Human Interaction** - *H. Friedrich, S. Münch, R. Dillman, S. Bocionek and M. Sassin* - 1996 |

| **Robust behaviorally correct learning** - *S. Jain* - 1999 |

| **Robust Classification for Imprecise Environments** - *Foster Provost and Tom Fawcett* - 2001 |

| **Robust Learning Aided by Context** - *John Case, Sanjay Jain, Matthias Ott, Arun Sharma and Frank Stephan* - 2000 |

| **Robust Learning Is Rich** - *Sanjay Jain, Carl Smith and Rolf Wiehagen* - 2001 |

| **Robust Learning - Rich and Poor** - *John Case, Sanjay Jain, Frank Stephan and Rolf Wiehagen* - 2001 |

| **Robust learning with infinite additional information** - *Susanne Kaufmann and Frank Stephan* - 2001 |

| **Robust learning with infinite additional information** - *Susanne Kaufmann and Frank Stephan* - 1997 |

| **Robust Learning with Missing Data** - *Marco Ramoni and Paola Sebastiani* - 2001 |

| **The robustness of the p-norm algorithms** - *Claudio Gentile and Nick Littlestone* - 1999 |

| **Robust Sensor Fusion: Analysis and Application to Audio Visual Speech Recognition** - *Javier R. Movellan and Paul Mineiro* - 1998 |

| **Robust separations in inductive inference** - *M. A. Fulk* - 1990 |

| **Robust trainability of single neurons** - *K. Höffgen and H. Simon* - 1992 |

| **Robust trainability of single neurons** - *Klaus-U. Höffgen, Hans-U. Simon and Kevin S. Van Horn* - 1995 |

| **The role of learning in autonomous robots** - *R. Brooks* - 1991 |

| **Rough Sets and Ordinal Classification** - *Jan C. Bioch and Viara Popova* - 2000 |

| **Round Robin Rule Learning** - *Johannes Fürnkranz* - 2001 |

| **Rule-Based Ensemble Solutions for Regression** - *Nitin Indurkhya and Sholom M. Weiss* - 2001 |

| **Rule Combination in Inductive Learning** - *L. Torgo* - 1993 |

| **Rule Discovery from fMRI Brain Images by Logical Regression Analysis** - *Hiroshi Tsukimoto, Mitsuru Kakimoto, Chie Morita and Yoshiaki Kikuchi* - 2001 |

| **Rule-Generating Abduction for Recursive Prolog** - *Kouichi Hirata* - 1994 |

| **Rule induction for semantic query optimization** - *Chun-Nan Hsu and Craig A. Knoblock* - 1994 |