找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Learning Theory; 17th Annual Conferen John Shawe-Taylor,Yoram Singer Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 2004 Boo

[復制鏈接]
查看: 27690|回復: 62
樓主
發(fā)表于 2025-3-21 18:33:05 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Learning Theory
副標題17th Annual Conferen
編輯John Shawe-Taylor,Yoram Singer
視頻videohttp://file.papertrans.cn/583/582820/582820.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Learning Theory; 17th Annual Conferen John Shawe-Taylor,Yoram Singer Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 2004 Boo
出版日期Conference proceedings 2004
關鍵詞Boolean function; Boosting; algorithmic learning; bayesian networks; computational learning; decision the
版次1
doihttps://doi.org/10.1007/b98522
isbn_softcover978-3-540-22282-8
isbn_ebook978-3-540-27819-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2004
The information of publication is updating

書目名稱Learning Theory影響因子(影響力)




書目名稱Learning Theory影響因子(影響力)學科排名




書目名稱Learning Theory網(wǎng)絡公開度




書目名稱Learning Theory網(wǎng)絡公開度學科排名




書目名稱Learning Theory被引頻次




書目名稱Learning Theory被引頻次學科排名




書目名稱Learning Theory年度引用




書目名稱Learning Theory年度引用學科排名




書目名稱Learning Theory讀者反饋




書目名稱Learning Theory讀者反饋學科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權限
沙發(fā)
發(fā)表于 2025-3-21 20:36:59 | 只看該作者
A Function Representation for Learning in Banach Spacesh spaces and show how this function representation naturally arises in that problem. Furthermore, we provide circumstances in which these representations are dense relative to the uniform norm and discuss how the parameters in such representations may be used to fit data.
板凳
發(fā)表于 2025-3-22 03:59:17 | 只看該作者
地板
發(fā)表于 2025-3-22 05:54:26 | 只看該作者
Regret Bounds for Hierarchical Classification with Linear-Threshold Functions the number of training examples and depends in a detailed way on the interaction between the process parameters and the taxonomy structure. Preliminary experiments on real-world data provide support to our theoretical results.
5#
發(fā)表于 2025-3-22 11:39:43 | 只看該作者
6#
發(fā)表于 2025-3-22 16:22:46 | 只看該作者
Concentration Bounds for Unigrams Language Modelarning algorithm is its expected per-word log-loss. We show that the leave-one-out method can be used for estimating the log-loss of the unigrams model with a PAC error of approximately ., for any distribution..We also bound the log-loss a priori, as a function of various parameters of the distribution.
7#
發(fā)表于 2025-3-22 18:49:46 | 只看該作者
8#
發(fā)表于 2025-3-23 00:30:34 | 只看該作者
Learning Classes of Probabilistic Automata stochastic languages. We show that a MA may generate a stochastic language that cannot be generated by a PFA, but we show also that it is undecidable whether a MA generates a stochastic language. Finally, we propose a learning algorithm for a subclass of PFA, called PRFA.
9#
發(fā)表于 2025-3-23 02:57:55 | 只看該作者
10#
發(fā)表于 2025-3-23 09:35:50 | 只看該作者
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-12 18:24
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
岳阳市| 惠来县| 九龙城区| 五常市| 高密市| 陈巴尔虎旗| 新昌县| 伊宁市| 万山特区| 尖扎县| 江门市| 潞城市| 和田县| 敦化市| 永清县| 雷州市| 本溪市| 建水县| 十堰市| 定安县| 平度市| 松潘县| 廊坊市| 大厂| 新蔡县| 沈丘县| 乾安县| 县级市| 惠水县| 雷山县| 依安县| 齐河县| 吉隆县| 绥滨县| 台前县| 彭州市| 新昌县| 西充县| 祁连县| 任丘市| 山西省|