Titlebook: Algorithmic Learning Theory; 14th International C Ricard Gavaldá,Klaus P. Jantke,Eiji Takimoto Conference proceedings 2003 Springer-Verlag

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書目名稱Algorithmic Learning Theory影響因子(影響力)




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書目名稱Algorithmic Learning Theory網(wǎng)絡(luò)公開度




書目名稱Algorithmic Learning Theory網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Algorithmic Learning Theory被引頻次




書目名稱Algorithmic Learning Theory被引頻次學(xué)科排名




書目名稱Algorithmic Learning Theory年度引用




書目名稱Algorithmic Learning Theory年度引用學(xué)科排名




書目名稱Algorithmic Learning Theory讀者反饋




書目名稱Algorithmic Learning Theory讀者反饋學(xué)科排名

無畏

Can Learning in the Limit Be Done Efficiently?the learner did already succeed. The resulting uncertainty may be prohibitive in many applications. We survey results to resolve this problem by outlining a new learning model, called .. Though pattern languages can neither be finitely inferred from positive data nor PAC-learned, our approach can be

赤字

自愛

On Ordinal VC-Dimension and Some Notions of Complexityomplexity—a variation on predictive complexity—and mind change complexity. The assumptions that . is closed under boolean operators and that . is compact often play a crucial role to establish connections between these concepts.

AGATE

罵人有污點(diǎn)

權(quán)宜之計(jì)

發(fā)酵

On the Learnability of Erasing Pattern Languages in the Query Model efficient than standard query learners. Moreover, when studying this new model in a more general context, interesting relations to Gold’s model of language learning from only positive data have been elaborated.

Terminal

Efficiently Learning the Metric with Side-Informationmputational complexity of the method severely limits its applicability to real machine learning tasks. In this paper we present an alternative solution for dealing with the problem of incorporating side-information. This side-information specifies pairs of examples belonging to the same class. The a

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