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Preface

2020 2020 IEEE International Conference on Big Data (Big Data)  
In addition, the conference features 39 workshops covering many emerging research directions in Big Data.  ...  We also sincerely hope that you will find ample opportunities to share ideas with one other and foster new research and innovations in big data. Prof.  ... 
doi:10.1109/bigdata50022.2020.9378384 fatcat:viqvvjh5kzawpkvwhxzwbcn3bu

Program Committee

2021 2021 IEEE International Conference on Big Data (Big Data)  
doi:10.1109/bigdata52589.2021.9671628 fatcat:c4zsduqldbde7ji75mkknoub44

[Copyright notice]

2021 2021 IEEE International Conference on Big Data (Big Data)  
The CPP handles the worldwide post-conference sales and distribution of IEEE-related conference publications to exclusively individuals (including IEEE members) and institutions (including libraries),  ...  We are pleased to inform you that your publication is eligible for inclusion in the IEEE Conference Publication Program (CPP).  ...  TITLING CONSISTENCY INFORMATION For the purpose of consistency, the title be used on this 2021 IEEE International Conference on Big Data (Big Data) must conference proceedings.  ... 
doi:10.1109/bigdata52589.2021.9671782 fatcat:wmbdciwaifgb7fvfp3douvu4bu

Addressing human bottlenecks in big data

Joseph M. Hellerstein
2014 2014 IEEE International Conference on Big Data (Big Data)  
The Big Data ecosystem presents two archetypal settings for answering this question: NoSQL distributed databases, and analytics on Hadoop.  ...  Today, the critical bottlenecks in data-driven organizations are human bottlenecks, measured in the costs of software developers, IT professionals, and data analysts.  ...  In 2012, Joe co-founded Trifacta, Inc(http://www.trifacta.com/company/people/), where he currently serves as Chief Strategy Officer. 2014 IEEE International Conference on Big Data 978-1-4799-5666-1/14  ... 
doi:10.1109/bigdata.2014.7004205 fatcat:o4yq2orxmrh4lcyat5fcp2rqwa

Towards a big data theory model

Marco Pospiech, Carsten Felden
2015 2015 IEEE International Conference on Big Data (Big Data)  
In a previous study we deduced an initial qualitative Big Data theory model based on expert interviews and grounded theory.  ...  Thereby, hypothesis are deduced and Big Data indicators presented. As a result, a Big Data theory model arises.  ...  Besides the origin of Big Data, the discussion exists, whether Big Data have an effect on the category strategy or not.  ... 
doi:10.1109/bigdata.2015.7363990 dblp:conf/bigdataconf/PospiechF15 fatcat:aeoc7vqkpvby7filjcevwmq5oq

Addressing data veracity in big data applications

Saima Aman, Charalampos Chelmis, Viktor Prasanna
2014 2014 IEEE International Conference on Big Data (Big Data)  
Such scenarios lead to partial data problem and raise the issue of data veracity in big data applications.  ...  Big data applications such as in smart electric grids, transportation, and remote environment monitoring involve geographically dispersed sensors that periodically send back information to central nodes  ...  Sensor based big data applications often encounter problems with respect to availability and timeliness of data [5] , where only partial data from sensors is available in real-time, and complete high  ... 
doi:10.1109/bigdata.2014.7004473 dblp:conf/bigdataconf/AmanCP14 fatcat:nbm6562bdzhblmbkwyqommhhn4

Unsupervised Risk for Privacy

Christophe Cerisara, Alfredo Cuzzocrea
2021 2021 IEEE International Conference on Big Data (Big Data)  
The current state-of-the-art methods, such as the ones based on differential privacy and training loss regularization, mainly propose approaches that try to improve the compromise between privacy guarantees  ...  We propose a new research direction that challenges this view, and that is based on novel approximations of the training objective of deep learning models.  ...  Université d'Excellence projects. 978-1-6654-3902-2/21/$31.00 ©2021 IEEE II.  ... 
doi:10.1109/bigdata52589.2021.9671539 fatcat:bkokfhevnjarvjk5ykybbambbq

Some examples of big data in railroad engineering

Allan M. Zarembski
2014 2014 IEEE International Conference on Big Data (Big Data)  
The railroad industry is an infrastructure intensive industry that relies on significant amounts of information and data to operate and maintain each railroad.  ...  This paper presents examples of collection, storage and use of "big data" in the railroad engineering environment.  ...  International Conference on Big Data 978-1-4799-5666-1/14/$31.00 ©2014 IEEE US railroads use the English system and use MilePost or MP as the primary location identifier. 2 Railroad routes can have  ... 
doi:10.1109/bigdata.2014.7004437 dblp:conf/bigdataconf/Zarembski14 fatcat:wgbvlqniffbpfj4ganbpibrnui

Low complexity sensing for big spatio-temporal data

Dongeun Lee, Jaesik Choi
2014 2014 IEEE International Conference on Big Data (Big Data)  
data.  ...  Many large scale sensor networks produce tremendous data, typically as massive spatio-temporal data streams.  ...  Thus, these sensors generate continuous flows of big sensing data that pose important challenges: how to sense and transmit massive data all in efficient manner.  ... 
doi:10.1109/bigdata.2014.7004248 dblp:conf/bigdataconf/LeeC14 fatcat:rwfjnid6tfdonbx5cfosiebsya

Moving past the "Wild West" era for Big Data

H. V. Jagadish
2015 2015 IEEE International Conference on Big Data (Big Data)  
Civilization is Based on Rules We can no longer do everything we can. We have to follow rules Alejandro Groenewold , CC-BY-NC-ND-2.0  ...  No Option to Exit • In the past, one could get a fresh start by: -Moving to a new place -Waiting till the past fades • Reputations can be rebuilt over time. • Big Data is universal and never forgets anything  ...  The data scientist's code of ethics We Should Own Our Destiny • I am proud of being a data scientist and excited about the good that Big Data can do. • If we do not self-regulate, there will be a public  ... 
doi:10.1109/bigdata.2015.7363733 dblp:conf/bigdataconf/Jagadish15 fatcat:5q6ocvzpojgwbdnslxfberj3gq

Enabling scientific data storage and processing on big-data systems

Saman Biookaghazadeh, Yiqi Xu, Shujia Zhou, Ming Zhao
2015 2015 IEEE International Conference on Big Data (Big Data)  
It also enables Hive to support standard queries on NetCDF data, transparently to users.  ...  Big-data systems are increasingly important for solving the data-driven problems in many science domains including geosciences.  ...  To the best of our knowledge, our work is the first to provide native support of widely used scientific data format on big-data systems.  ... 
doi:10.1109/bigdata.2015.7363978 dblp:conf/bigdataconf/BiookaghazadehX15 fatcat:cgp433manne55daz6n4ll2jqdi

Message from the IEEE Big Data Congress 2019 Chairs

2019 2019 IEEE International Congress on Big Data (BigDataCongress)  
The IEEE Big Data Congress is now recognized as a mainstream event covering the many dimensions of Big Data research, including Models and Algorithms, Data Systems Engineering, Big Data Management, Security  ...  This year's conference also accepted work-in-progress (WiP) paper submissions.  ...  We wish you all a productive and enjoyable conference in Milan and hope you find these proceedings a valuable source of information on Big Data research.  ... 
doi:10.1109/bigdatacongress.2019.00011 fatcat:ktr3zfvrvncsffh5neur3tvlii

Conference Organization

2015 2015 IEEE International Conference on Multimedia Big Data  
The more papers you review, the more internal consistency you have. With a sample that big, past bias goes away. If your sample is too small, you might wind up with everything near the bar.  ...  But this would be a big change that would upset the apple cart of career advancement in both academia and the corporate world. I think it would be a big controversy in the community.  ... 
doi:10.1109/bigmm.2015.6 fatcat:qzptktkaa5cchofhufo6xooqba

Ordinal Hyperplane Loss

Bob Vanderheyden, Ying Xie
2018 2018 IEEE International Conference on Big Data (Big Data)  
This research presents the development of a new framework for analyzing ordered class data, commonly called "ordinal class" data.  ...  data scientists may be asked to develop predictive classifiers.  ...  As data set size, increases to today's "Big Data" levels of millions or billions of rows of data, the computation complexity, in submitting the entire dataset, in a single pass through the DNN is not possible  ... 
doi:10.1109/bigdata.2018.8622079 dblp:conf/bigdataconf/VanderheydenX18 fatcat:yj4ttuibt5ayvefjv6wsmfhb54

Learning with Missing Data

Carlos A. Escobar, Jorge Arinez, Daniela Macias, Ruben Morales-Menendez
2020 2020 IEEE International Conference on Big Data (Big Data)  
On the other hand, imputing the missing records is a better approach, but it should be used with great caution, as it relies on often unrealistic specific assumptions which can potentially bias results  ...  Many real-world data sets contain missing values, therefore, learning with incomplete data sets is a common challenge faced by data scientists.  ...  A circumstance that may cause missing data could vary from one condition to another.  ... 
doi:10.1109/bigdata50022.2020.9377785 fatcat:hrgflnmkdrfxtcky7brjxiqvfq
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