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Computational learning theory
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191	Laurie P. Dringus, Ph.D. Professor, Graduate School of Computer and Information Sciences Nova Southeastern University Carl DeSantis Building, 4th floor (office number[removed]College Avenue Ft. Lauderdale, FL 33314 Add to Reading List Source URL: www.scis.nova.edu Language: English - Date: 2014-03-26 11:57:02 Pedagogy Learning Human–computer interaction E-learning Computer-mediated communication Asynchronous learning Learning analytics Blended learning Computational learning theory Education Knowledge Distance education
192	Using Theory Formation Techniques for the Invention of Fictional Concepts Flaminia Cavallo, Alison Pease, Jeremy Gow, Simon Colton Computational Creativity Group Department of Computing Imperial College, London Add to Reading List Source URL: ccg.doc.gold.ac.uk Language: English - Date: 2013-08-16 08:43:42 Philosophy of language Semantics Thought Problem solving Knowledge representation Concept learning Concept Creativity Computational creativity Cognition Mind Science
193	Machine Learning for Adversarial Agent Microworlds Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-15 18:49:06 Artificial intelligence Computational neuroscience Reinforcement learning Simulation Q-learning Temporal difference learning Game theory Machine learning Reinforcement Statistics Science Mathematics
194	VC-dimension for characterizing classifiers Note to other teachers and users of these slides. Andrew would be delighted if you found this source material useful in Add to Reading List Source URL: www.autonlab.org Language: English - Date: 2008-07-07 16:16:22 Statistics Dimension Statistical classification VC dimension Shattered set Vector space Algebra Mathematics Computational learning theory
195	Online Learning with Kernels Jyrki Kivinen Alex J. Smola Robert C. Williamson Research School of Information Sciences and Engineering Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 08:39:23 Statistical theory Computational statistics Neural networks Computational neuroscience Support vector machine Stochastic gradient descent Perceptron Loss function Robust statistics Statistics Machine learning Econometrics
196	CURRICULUM VITAE of ROBERT CRAIG HOLTE (August 12, 2014) Personal Information current occupation: Professor, tenured Add to Reading List Source URL: webdocs.cs.ualberta.ca Language: English - Date: 2014-08-13 18:17:59 Holte Baronets Holte Fringe search Applied mathematics Association for the Advancement of Artificial Intelligence Computational learning theory Robert Holt Jonathan Schaeffer Holt Artificial intelligence Computer science Symposium on Combinatorial Search
197	The VC-Dimension and Pseudodimension of Two-Layer Neural Networks with Discrete Inputs Peter L. Bartlett Robert C. Williamson Department of Systems Engineering Research School of Information Sciences and Engineering Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-03-22 04:19:25 Mathematics Radial basis function Sigmoid function Computational learning theory VC dimension Neural networks Statistics Applied mathematics
198	Publications List Johannes F¨urnkranz The key publications can be categorized into inductive rule learning [4, 20, 22, 31, 34, 37, 38, 40, 44, 51, 56, 159], preference learning [5, 12, 19, 21, 25, 27, 28, 77, 93, 94], r Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2015-02-27 18:55:47 Computational statistics Statistics ECML PKDD Web mining International Conference on Machine Learning Computational learning theory Data stream mining Data mining Machine learning Artificial intelligence
199	Learnability of Probabilistic Automata via Oracles Omri Guttman ? , S.V.N. Vishwanathan, and Robert C. Williamson Statistical Machine Learning Program National ICT Australia RSISE, Australian National University Add to Reading List Source URL: users.cecs.anu.edu.au Language: English - Date: 2005-05-22 19:18:42 Mathematics Automata theory Algorithm Markov chain Computational learning theory Symbol Kullback–Leibler divergence Statistics Theoretical computer science Applied mathematics
200	A Note on Phase Transitions and Computational Pitfalls of Learning from Sequences Antoine Cornu´ejols1 & Mich`ele Sebag2 1 AgroParisTech / INRA Add to Reading List Source URL: eprints.pascal-network.org Language: English - Date: 2008-01-16 05:03:29 Computer science Applied mathematics Deterministic finite automaton Finite-state machine Grammar induction Algorithm Sequence Powerset construction Automata theory Models of computation Theoretical computer science

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