找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Discovery Science; 15th International C Jean-Gabriel Ganascia,Philippe Lenca,Jean-Marc Pet Conference proceedings 2012 Springer-Verlag Berl

[复制链接]
查看: 39558|回复: 62
发表于 2025-3-21 16:38:49 | 显示全部楼层 |阅读模式
书目名称Discovery Science
副标题15th International C
编辑Jean-Gabriel Ganascia,Philippe Lenca,Jean-Marc Pet
视频video
概述Up-to-date results.Fast-track conference proceedings.State-of-the-art research
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Discovery Science; 15th International C Jean-Gabriel Ganascia,Philippe Lenca,Jean-Marc Pet Conference proceedings 2012 Springer-Verlag Berl
描述This book constitutes the refereed proceedings of the 15th International Conference on Discovery Science, DS 2012, held in Lyon, France, in October 2012. The 22 papers presented in this volume were carefully reviewed and selected from 46 submissions. The field of discovery science aims at inducing and validating new scientific hypotheses from data. The scope of this conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, tools for supporting the human process of discovery in science, as well as their application to knowledge discovery.
出版日期Conference proceedings 2012
关键词XML mining; autonomous exploration; data mining; huge network; reinforcement learning; algorithm analysis
版次1
doihttps://doi.org/10.1007/978-3-642-33492-4
isbn_softcover978-3-642-33491-7
isbn_ebook978-3-642-33492-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2012
The information of publication is updating

书目名称Discovery Science影响因子(影响力)




书目名称Discovery Science影响因子(影响力)学科排名




书目名称Discovery Science网络公开度




书目名称Discovery Science网络公开度学科排名




书目名称Discovery Science被引频次




书目名称Discovery Science被引频次学科排名




书目名称Discovery Science年度引用




书目名称Discovery Science年度引用学科排名




书目名称Discovery Science读者反馈




书目名称Discovery Science读者反馈学科排名




单选投票, 共有 0 人参与投票
 

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

您所在的用户组没有投票权限
发表于 2025-3-21 23:45:28 | 显示全部楼层
Recent Developments in Pattern Miningquent itemsets have been proposed. These exhaustive algorithms, however, all suffer from the pattern explosion problem. Depending on the minimal support threshold, even for moderately sized databases, millions of patterns may be generated. Although this problem is by now well recognized in te patter
发表于 2025-3-22 02:15:23 | 显示全部楼层
发表于 2025-3-22 05:21:14 | 显示全部楼层
Large Scale Spectral Clustering Using Resistance Distance and Spielman-Teng Solverse price for this promise is the computational cost .(..) for computing the eigen-decomposition of the graph Laplacian matrix - so far a necessary subroutine for spectral clustering. In this paper we bypass the eigen-decomposition of the original Laplacian matrix by leveraging the recently introduced
发表于 2025-3-22 09:49:45 | 显示全部楼层
Prediction of Quantiles by Statistical Learning and Application to GDP Forecastingnctions. In a first time, we show that the Gibbs estimator is able to predict as well as the best predictor in a given family for a wide set of loss functions. In particular, using the quantile loss function of [1], this allows to build confidence intervals. We apply these results to the problem of
发表于 2025-3-22 15:41:12 | 显示全部楼层
Policy Search in a Space of Simple Closed-form Formulas: Towards Interpretability of Reinforcement Llgorithm over a space of simple closed-form formulas that are used to rank actions. We formalize the search for a high-performance policy as a multi-armed bandit problem where each arm corresponds to a candidate policy canonically represented by its shortest formula-based representation. Experiments
发表于 2025-3-22 17:46:02 | 显示全部楼层
Towards Finding Relational Redescriptionstional dataset. By extending redescription mining beyond propositional and real-valued attributes, it provides a powerful tool to match different relational descriptions of the same concept. As a first step towards solving this general task, we introduce an efficient algorithm that mines one descrip
发表于 2025-3-22 22:06:50 | 显示全部楼层
发表于 2025-3-23 01:51:26 | 显示全部楼层
A Trim Distance between Positions in Nucleotide Sequencesg the indices of nucleotide sequences as labels of leaves with the nucleotides occurring in a position, we formulate a . between two positions in nucleotide sequences as the LCA-preserving distance between the trimmed phylogenetic trees according to nucleotides occurring in the positions. Finally, w
发表于 2025-3-23 05:39:03 | 显示全部楼层
Data Squashing for HSV Subimages by an Autonomous Mobile Robotakes during a navigation of dozens of minutes. The subimages are managed according to a similarity measure between a pair of subimages, which is based on a method for quantizing HSV colors. The data index structure has been inspired by the CF tree of BIRCH, which is an early work in data squashing,
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-5-11 01:03
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表