开课单位--荷兰乌得勒支大学
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The launch of CEMROL: the charms and challenges of developing an academic crowdsourcing platform[CEMROL的推出:开发学术众包平台的魅力和挑战]
  Karen Hollewand(荷兰乌得勒支大学) The launch of CEMROL: the charms and challenges of developing an academic crowdsourcing platform
热度:30

2
Towards a Universe of Local Time Machines[走向本地时间机器的宇宙]
  Toine Pieters(荷兰乌得勒支大学) Towards a Universe of Local Time Machines
热度:28

3
Tracing conceptual change in messy data (2): Self-reliance as boon and bane[在凌乱的数据中追踪概念的变化(2):自力更生是好事还是坏事]
   Joris van Eijnatten(荷兰乌得勒支大学) As a cultural historian with an interest in demonstrating the usefulness of an assortment of digital humanities tools and techniques to researchers, b...
热度:38

4
The Project MinE data browser: bringing whole-genome sequencing data in ALS to researchers and the public[项目矿山数据浏览器:将ALS中的全基因组测序数据带给研究人员和公众]
   Rick A. A. van der Spek(荷兰乌得勒支大学) Project MinE is an international collaboration with the aim of whole-genome sequencing 15,000 amyotrophic lateral sclerosis (ALS) patients and 7,500 c...
热度:49

5
ATXN1: expanding the spectrum of polyglutamine repeats in ALS[ATXN1:扩大ALS中多聚谷氨酰胺重复序列的范围]
   Gijs Tazelaar(荷兰乌得勒支大学) Objective: Polyglutamine proteins can cause a wide range of neurodegenerative disorders upon long-range expansions such as Huntington’s disease ...
热度:91

6
Empirical Bayesian test for the smoothness[光滑度的经验贝叶斯检验]
  Eduard Belitser(荷兰乌得勒支大学) In the context of adaptive nonparametric curve estimation problem, a common assumption is that the function (signal) to estimate belongs to a nested f...
热度:50

7
Characteristic Relational Patterns[特征的关系模式]
  Arne Koopman(荷兰乌得勒支大学) Research in relational data mining has two major directions: finding global models of a relational database and the discovery of local relational patt...
热度:49

8
Brief presentation of editors and respective Journals[编辑和各期刊的简要介绍]
  Max A. Viergever;Bruce Wheeler;Eberhard Neumann; Jos A. E. Spaan;Gregor Serša;Nillo Saranummi;Carmelina Ruggiero(荷兰乌得勒支大学)
热度:52

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Parameter Learning for Bayesian Networks with Strict Qualitative Influences[严格定性影响的贝叶斯网络的参数学习]
  Ad Feelders(荷兰乌得勒支大学) We propose a new method for learning the parameters of a Bayesian network with qualitative influences. The proposed method aims to remove unwanted (co...
热度:45

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Non-Redundant Subgroup Discovery in Large and Complex Data[大型复杂数据中的非冗余子群发现]
  Matthijs van Leeuwen(荷兰乌得勒支大学) Large and complex data is challenging for most existing discovery algorithms, for several reasons. First of all, such data leads to enormous hypothesi...
热度:69
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