Conferences in DBLP
J. Stephen Judd Learning in Neural Networks. [Citation Graph (0, 0)][DBLP ] Conf ] Avrim Blum , Ronald L. Rivest Training a 3-Node Neural Network is NP-Complete. [Citation Graph (0, 0)][DBLP ] Conf ] P. Raghavan Learning in Threshold Networks. [Citation Graph (0, 0)][DBLP ] Conf ] Leslie G. Valiant Functionality in Neural Nets. [Citation Graph (0, 0)][DBLP ] Conf ] David Haussler , Michael J. Kearns , Nick Littlestone , Manfred K. Warmuth Equivalence of Models for Polynomial Learnability. [Citation Graph (0, 0)][DBLP ] Conf ] Nathan Linial , Yishay Mansour , Ronald L. Rivest Results on Learnability and the Vapnick-Chervonenkis Dimension. [Citation Graph (0, 0)][DBLP ] Conf ] Ronald L. Rivest , Robert H. Sloan Learning Complicated Concepts Reliably and Usefully. [Citation Graph (0, 0)][DBLP ] Conf ] Gyora M. Benedek , Alon Itai Learnability by Fixed Distributions. [Citation Graph (0, 0)][DBLP ] Conf ] Robert H. Sloan Types of Noise in Data for Concept Learning. [Citation Graph (0, 0)][DBLP ] Conf ] George Shackelford , Dennis Volper Learning k-DNF with Noise in the Attributes. [Citation Graph (0, 0)][DBLP ] Conf ] Jeffrey Scott Vitter , Jyh-Han Lin Learning in Parallel. [Citation Graph (0, 0)][DBLP ] Conf ] Stéphane Boucheron , Jean Sallantin Some Remarks About Space-Complexity of Learning, and Circuit Complexity of Recognizing. [Citation Graph (0, 0)][DBLP ] Conf ] Andrzej Ehrenfeucht , David Haussler , Michael J. Kearns , Leslie G. Valiant A General Lower Bound on the Number of Examples Needed for Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Haim Schweitzer Non-Learnable Classes of Boolean Formulae That Are Closer Under Variable Permutation. [Citation Graph (0, 0)][DBLP ] Conf ] Dana Angluin Learning With Hints. [Citation Graph (0, 0)][DBLP ] Conf ] Andrzej Ehrenfeucht , David Haussler Learning Decision Trees from Random Examples. [Citation Graph (0, 0)][DBLP ] Conf ] John Case The Power of Vacillation. [Citation Graph (0, 0)][DBLP ] Conf ] Stuart A. Kurtz , James S. Royer Prudence in Language Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Robert P. Daley Transformation of Probabilistic Learning Strategies into Deterministic Learning Strategies. [Citation Graph (0, 0)][DBLP ] Conf ] William I. Gasarch , Carl H. Smith Learning via Queries. [Citation Graph (0, 0)][DBLP ] Conf ] William I. Gasarch , Ramesh K. Sitaraman , Carl H. Smith , Mahendran Velauthapillai Learning Programs with an Easy to Calculate Set of Errors. [Citation Graph (0, 0)][DBLP ] Conf ] John C. Cherniavsky , Mahendran Velauthapillai , Richard Statman Inductive Inference: An Abstract Approach. [Citation Graph (0, 0)][DBLP ] Conf ] Ranan B. Banerji Learning Theories in a Subset of a Polyadic Logic. [Citation Graph (0, 0)][DBLP ] Conf ] David Haussler , Nick Littlestone , Manfred K. Warmuth Predicting {0, 1}-Functions on Randomly Drawn Points. [Citation Graph (0, 0)][DBLP ] Conf ] Philip D. Laird Efficient Unsupervised Learning. [Citation Graph (0, 0)][DBLP ] Conf ] Alfredo De Santis , George Markowsky , Mark N. Wegman Learning Probabilistic Prediction Functions. [Citation Graph (0, 0)][DBLP ] Conf ] Yasubumi Sakakibara Learning Context-Free Grammars from Structural Data in Polynomial Time. [Citation Graph (0, 0)][DBLP ] Conf ] Assaf Marron Learning Pattern Languages from a Single Initial Example and from Queries. [Citation Graph (0, 0)][DBLP ] Conf ] Ming Li , Umesh V. Vazirani On the Learnability of Finite Automata. [Citation Graph (0, 0)][DBLP ] Conf ] Oscar H. Ibarra , Tao Jiang Learning Regular Languages From Counterexamples. [Citation Graph (0, 0)][DBLP ] Conf ] Sara Porat , Jerome A. Feldman Learning Automata from Ordered Examples. [Citation Graph (0, 0)][DBLP ] Conf ] 