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检索条件"机构=Institute of Data Analysis and Process Design"
31 条 记 录,以下是11-20 订阅
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Assessing Keyness using Permutation Tests
arXiv
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arXiv 2023年
作者: Mildenberger, Thoralf Institute of Data Analysis and Process Design Switzerland ZHAW Zurich University of Applied Sciences Switzerland
We propose a resampling-based approach for assessing keyness in corpus linguistics based on suggestions by Gries (2006, 2022). Traditional approaches based on hypothesis tests (e.g. Likelihood Ratio) model the copora ... 详细信息
来源: 评论
High-Frequency Causality in the VIX Index and its derivatives: Empirical Evidence
arXiv
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arXiv 2022年
作者: Farokhnia, Kia Osterrieder, Joerg Institute of Data Analysis and Process Design School of Engineering Zurich University of Applied Sciences Switzerland
In February 2018, the VIX index has seen its largest ever increase and has lead to significant losses for some major volatility-related products. Despite many efforts, the precise underlying reasons are yet to be disc... 详细信息
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Approximative Modelling of Manufacturing Systems
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IFAC Proceedings Volumes 2003年 第3期36卷 143-148页
作者: Christoph Heitz Institute for Data Analysis and Process Design Zurich University of Applied Sciences Winterthur IPLnet: Swiss National Competence Network for Integrated Production and Logistics
A new model for an approximative description of a production line is presented. Instead of a bottom-up modelling, an approach is presented which allows the modelling of large parts of the production line as a single &... 详细信息
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Artificial neural networks to impute rounded zeros in compositional data
arXiv
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arXiv 2020年
作者: Templ, Matthias Institute of Data Analysis and Process Design Zurich University of Applied Sciences Rosenstrasse 3 WinterthurCH-8401 Switzerland
Methods of deep learning have become increasingly popular in recent years, but they have not arrived in compositional data analysis. Imputation methods for compositional data are typically applied on additive, centere... 详细信息
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Online sequential extreme learning machines for fault detection
Online sequential extreme learning machines for fault detect...
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International Conference on Prognostics and Health Management, PHM
作者: Yang Hu Olga Fink Thomas Palmé Institute for Data Analysis and Process Design (IDP) Zurich University of Applied Sciences Winterthur Switzerland General Electric (GE) Baden Switzerland
In this paper, we propose the application of a new fault detection approach with a sequential updating function under new operating conditions or natural evolving degradation processes. The proposed approach is based ... 详细信息
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Gradual (In)Compatibility of Fairness Criteria
arXiv
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arXiv 2021年
作者: Hertweck, Corinna Räz, Tim Institute for Data Analysis and Process Design Zurich University of Applied Sciences Winterthur Switzerland Department of Informatics University of Zurich Zurich Switzerland Institute of Philosophy University of Bern Bern Switzerland
Impossibility results show that important fairness measures (independence, separation, sufficiency) cannot be satisfied at the same time under reasonable assumptions. This paper explores whether we can satisfy and/or ... 详细信息
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Greening urban logistics: Introducing a method to evaluate optimised decoupling hub locations
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Transportation Research Procedia 2023年 72卷 572-579页
作者: Maike Scherrer Albert Steiner Viola Rühlin Zurich University of Applied Sciences School of Engineering Institute of Sustainable Development Technikumstrasse 9 8401 Winterthur Switzerland Zurich University of Applied Sciences School of Engineering Institute of Data Analysis and Process Design Rosenstrasse 3 8401 Winterthur Switzerland
Sustainable urban logistics has become challenging over the course of the last decades due to logistics sprawl and increased demands of goods in urban areas. To overcome this problem, a fine-grained network of decoupl... 详细信息
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Quality assessment of Affymetrix GeneChip data using the EM algorithm and a naïve Bayes classifier
Quality assessment of Affymetrix GeneChip data using the EM ...
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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
作者: Howard, Brian E. Sick, Beate Perera, Imara Yang, Ju Im Winter-Sederoff, Heike Heber, Steffen Bioinformatics Research Center North Carolina State University Raleigh NC United States Institute of Data Analysis and Process Design Zurich University of Applied Science Winterthur Winterthur Switzerland Department of Plant Biology North Carolina State University Raleigh NC United States Department of Computer Science North Carolina State University Raleigh NC United States
Recent research has demonstrated the utility of using supervised classification systems for automatic identification of low quality microarray data. However, this approach requires annotation of a large training set b... 详细信息
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Deep Interpretable Ensembles
arXiv
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arXiv 2022年
作者: Kook, Lucas Götschi, Andrea Baumann, Philipp F. M. Hothorn, Torsten Sick, Beate Epidemiology Biostatistics & Prevention Institute University of Zurich CH-8001 Switzerland Institute for Data Analysis and Process Design Zurich University of Applied Sciences CH-8400 Switzerland KOF Swiss Economic Institute ETH Zurich CH-8092 Switzerland
Ensembles improve prediction performance and allow uncertainty quantification by aggregating predictions from multiple models. In deep ensembling, the individual models are usually black box neural networks, or recent... 详细信息
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Deep transformation models for functional outcome prediction after acute ischemic stroke
arXiv
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arXiv 2022年
作者: Herzog, Lisa Kook, Lucas Götschi, Andrea Petermann, Katrin Hänsel, Martin Hamann, Janne Dürr, Oliver Wegener, Susanne Sick, Beate Epidemiology Biostatistics & Prevention Institute University of Zurich Switzerland Institute for Data Analysis and Process Design Zurich University of Applied Sciences Switzerland Department of Neurology University Hospital Zurich Switzerland Insitute for Optical Systems Konstanz University of Applied Sciences Germany
In many medical applications, interpretable models with high prediction performance are sought. Often, those models are required to handle semi-structured data like tabular and image data. We show how to apply deep tr... 详细信息
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