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Browse All Reviews > Computing Methodologies (I) > Artificial Intelligence (I.2) > Learning (I.2.6) > Concept Learning (I.2.6...)
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1-10 of 21
Reviews about "Concept Learning (I.2.6...)":
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On equivalence of conceptual scaling and generalized one-sided concept lattices Butka P., Pócs J., Pócsová J. Information Sciences 25957-70, 2014. Type: Article
A technical account with mathematical proofs, this paper shows that the methods of conceptual scaling and generalized one-sided concept lattices are equivalent....
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Jun 3 2014 |
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A reinforcement learning algorithm based on policy iteration for average reward: empirical results with yield management and convergence analysis Gosavi A. Machine Learning 55(1): 5-29, 2004. Type: Article
An algorithm for solving average reward Markov and semi-Markov decision problems is presented in this paper. The algorithm is asynchronous and model free, and is capable of cooperating with a nearest neighbor approach to manage large s...
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Jul 28 2005 |
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Incremental learning with partial instance memory Maloof M., Michalski R. Artificial Intelligence 154(1-2): 95-126, 2004. Type: Article
The primary problem with online incremental machine learning methods is the tradeoff between predictive accuracy and the increasing computational costs of keeping increasing amounts of training data....
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Nov 3 2004 |
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Queries revisited Angluin D. Theoretical Computer Science 313(2): 175-194, 2004. Type: Article
A concept is a subset of a finite domain. We want to bind the number of questions that have to be asked in order to identify a concept that comes from a known concept class. These bounds depend on which kinds of questions can be asked....
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May 19 2004 |
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Online learning in online auctions Blum A., Kumar V., Rudra A., Wu F. Discrete algorithms (Proceedings of the fourteenth annual ACM-SIAM symposium, Baltimore, Maryland, Jan 12-14, 2003) 202-204, 2003. Type: Proceedings
Performance of an online auction can be improved by an algorithm that learns from the set of bids already made. An online auction receives bids, and deals with each individually, deciding whether to accept a bid or wait for a higher on...
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Dec 31 2003 |
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Unsupervised Learning of Human Motion Song Y., Goncalves L., Perona P. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(7): 814-827, 2003. Type: Article
A method for learning a probabilistic model of human motion, in an unsupervised fashion, from unlabeled cluttered data is presented. The models obtained are mixtures of Gaussian models and conditional independence, described by a decom...
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Dec 11 2003 |
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Support vector machine active learning with applications to text classification Tong S., Koller D. The Journal of Machine Learning Research 2(1): 45-66, 2001. Type: Article
This well-written paper is a major contribution to the field of active learning by support vector machines (SVMs). Usually, machine learning methods are passive: machines learn from a set of labeled training data. In active learning, h...
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Nov 4 2003 |
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A bio-inspired robotic mechanism for autonomous locomotion in unconventional environments Maravall D., de Lope J. In Autonomous robotic systems. Heidelberg, Germany: Physica-Verlag GmbH, 2003. Type: Book Chapter
Maravall and de Lope describe a robotic model capable of navigating along aerial power, telephone, or railroad lines, as well as in reticulated structures....
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Sep 17 2003 |
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Scale-sensitive dimensions, uniform convergence, and learnability Alon N., Ben-David S., Cesa-Bianchi N., Haussler D. Journal of the ACM 44(4): 615-631, 1997. Type: Article
Inspired by Valiant’s PAC learning model, the authors, using discretization techniques, seek a convergence of distribution-free expectations over classes of random variables. Real-valued functions (such as Glivenko-Cantelli c...
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Oct 1 1998 |
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Learnable classes of categorial grammars Kanazawa M., Cambridge University Press, New York, NY, 1998. Type: Book (9781575860978)
The focus of this monograph is on learning categorial grammars from sequences of positive examples presented in the form of functor-argument structures. Sakakibara [1] has demonstrated that the class of reversible context-free grammars...
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Jul 1 1998 |
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