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Titlebook: Computational Learning Theory; 15th Annual Conferen Jyrki Kivinen,Robert H. Sloan Conference proceedings 2002 Springer-Verlag Berlin Heidel

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發(fā)表于 2025-3-21 18:03:38 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Computational Learning Theory
副標(biāo)題15th Annual Conferen
編輯Jyrki Kivinen,Robert H. Sloan
視頻videohttp://file.papertrans.cn/233/232578/232578.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Learning Theory; 15th Annual Conferen Jyrki Kivinen,Robert H. Sloan Conference proceedings 2002 Springer-Verlag Berlin Heidel
出版日期Conference proceedings 2002
關(guān)鍵詞Boosting; Internet; Markov decision process; Variable; algorithmic learning; algorithms; classification; co
版次1
doihttps://doi.org/10.1007/3-540-45435-7
isbn_softcover978-3-540-43836-6
isbn_ebook978-3-540-45435-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2002
The information of publication is updating

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




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




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




書目名稱Computational Learning Theory被引頻次




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Entropy, Combinatorial Dimensions and Random Averages function-class setup. Using this parameter we establish entropy bounds for subsets of the .-dimensional unit cube, and in particular, we present new bounds on the empirical covering numbers and gaussian averages associated with classes of functions in terms of the fat-shattering dimension.
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Path Kernels and Multiplicative Updatesroducts for all paths are summed. We also have a set of probabilities on the edges so that the outflow from each node is one. We then discuss multiplicative updates on these graphs where the prediction is essentially a kernel computation and the update contributes a factor to each edge. Now the tota
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Learning Tree Languages from Text2000 paper is generalizable from the case of string languages towards tree languages, hence providing a large source of identifiable classes of regular tree languages. Each of these classes can be characterized in various ways. Moreover, we present a generic inference algorithm with polynomial updat
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Polynomial Time Inductive Inference of Ordered Tree Patterns with Internal Structured Variables fromtured pattern in such tree structured data, we propose an ordered tree pattern, called a term tree, which is a rooted tree pattern consisting of ordered children and internal structured variables. A term tree is a generalization of standard tree patterns representing first order terms in formal logi
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