Results 231 to 240 of about 3,913 (266)
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2003
This chapter discusses usability in terms of the concept of learnability, that is, what makes the content of an online learning site learnable? It considers three core issues underlying learnability: learning theory, instructional design, and curriculum choices. For learning, it proposes a model integrating comprehension, interest, and memorizing.
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This chapter discusses usability in terms of the concept of learnability, that is, what makes the content of an online learning site learnable? It considers three core issues underlying learnability: learning theory, instructional design, and curriculum choices. For learning, it proposes a model integrating comprehension, interest, and memorizing.
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Learnability in information design
Proceedings of the 19th annual international conference on Computer documentation, 2001Design of information used for technical communication of complex products should consider how learnable that information is, and strive to deliver materials that are inherently learnable.The speed of information interchange and the demands of the workplace and school curricula require increasingly minimalist approaches to the material that is made ...
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The Learnability of Naive Bayes
2000Naive Bayes is an efficient and effective learning algorithm, but previous results show that its representation ability is severely limited since it can only represent certain linearly separable functions in the binary domain. We give necessary and sufficient conditions on linearly separable functions in the binary domain to be learnable by Naive Bayes
Huajie Zhang +2 more
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Planar Languages and Learnability
2006Strings can be mapped into Hilbert spaces using feature maps such as the Parikh map. Languages can then be defined as the pre-image of hyperplanes in the feature space, rather than using grammars or automata. These are the planar languages. In this paper we show that using techniques from kernel-based learning, we can represent and efficiently learn ...
Clark, Alexander +3 more
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2000
Recent theories suggest that language acquisition is assisted by the evolution of languages towards forms that are easily learnable. In this paper, we evolve combinatorial languages which can be learned by a recurrent neural network quickly and from relatively few examples. Additionally, we evolve languages for generalization in different "worlds", and
Tonkes, B., Blair, A. D., Wiles, J. H.
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Recent theories suggest that language acquisition is assisted by the evolution of languages towards forms that are easily learnable. In this paper, we evolve combinatorial languages which can be learned by a recurrent neural network quickly and from relatively few examples. Additionally, we evolve languages for generalization in different "worlds", and
Tonkes, B., Blair, A. D., Wiles, J. H.
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Iterative Learning Control for Discrete-Time Systems With Full Learnability
IEEE Transactions on Neural Networks and Learning Systems, 2022Yuanshi Zheng, Xiaoe Ruan
exaly
On Learnability of Decision Tables
2004The article is exploring the learnabilty issues of decision tables acquired from data within the frameworks of rough set and of variable precision rough set models. Measures of learning problem complexity and of learned table domain coverage are proposed.
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On the learnability of shuffle ideals.
J. Mach. Learn. Res., 2013PAC learning of unrestricted regular languages is long known to be a difficult problem. The class of shuffle ideals is a very restricted subclass of regular languages, where the shuffle ideal generated by a string u is the collection of all strings containing u as a subsequence.
Eisenstat, Sarah Charmian +3 more
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