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 Christophe G Giraud-Carrier

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Average citations per article4.80
Citation Count408
Publication count85
Publication years1993-2016
Available for download8
Average downloads per article161.63
Downloads (cumulative)1,293
Downloads (12 Months)125
Downloads (6 Weeks)29
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86 results found Export Results: bibtexendnoteacmrefcsv

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1
January 2018 Machine Learning: Volume 107 Issue 1, January 2018
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 1

This article serves as an introduction to the Special Issue on Metalearning and Algorithm Selection. The introduction is divided into two parts. In the the first section, we give an overview of how the field of metalearning has evolved in the last 1---2 decades and mention how some of the ...
Keywords: Algorithm selection and configuration, Automated ensemble construction, Metalearning, Hyperparameter optimization

2
November 2016 IEEE Transactions on Parallel and Distributed Systems: Volume 27 Issue 11, November 2016
Publisher: IEEE Press
Bibliometrics:
Citation Count: 2

Among uncertain graph queries, reachability, i.e., the probability that one vertex is reachable from another, is likely the most fundamental one. Although this problem has been studied within the field of network reliability, solutions are implemented on a single computer and can only handle small graphs. However, as the size ...

3
December 2015 Applied Intelligence: Volume 43 Issue 4, December 2015
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 1

Currently available algorithms for data streams classification are mostly designed to deal with precise and complete data. However, data in many real-life applications is naturally uncertain due to inherent instrument inaccuracy, wireless transmission error, and so on. We propose UELM-MapReduce, a parallel ensemble classifier based on Extreme Learning Machine (ELM) ...
Keywords: Ensemble classifier, Extreme learning machine, Classification, MapReduce, Concept drift, Uncertain data streams

4
November 2015 Knowledge and Information Systems: Volume 45 Issue 2, November 2015
Publisher: Springer-Verlag New York, Inc.
Bibliometrics:
Citation Count: 0

Up to now, most campaign contribution data have been reported at the level of the donation. While these are interesting, one often needs to have information at the level of the donor. Obtaining information at that level is difficult as there is neither a unique repository of donations nor any ...
Keywords: Campaign contributions, Political data, Record linkage, Domain knowledge, Multiset distance

5 published by ACM
September 2015 BCB '15: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 4,   Downloads (12 Months): 6,   Downloads (Overall): 27

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This short paper introduces the rationale for a workshop on computational health science, and provides a brief overview of the workshop's content. We point out some of the recent research on mining social media data for health, define what we mean by computational health science, and argue the value of ...
Keywords: workshop, computational health science, computing, health science, multidisciplinary research

6
September 2015 MetaSel'15: Proceedings of the 2015 International Conference on Meta-Learning and Algorithm Selection - Volume 1455
Publisher: CEUR-WS.org
Bibliometrics:
Citation Count: 0

The quality of a model induced by a learning algorithm is dependent upon the training data and the hyperparameters supplied to the learning algorithm. Prior work has shown that a model's quality can be significantly improved by filtering out low quality instances or by tuning the learning algorithm hyperparameters. The ...

7
December 2014 International Journal of Data Analysis Techniques and Strategies: Volume 6 Issue 4, December 2014
Publisher: Inderscience Publishers
Bibliometrics:
Citation Count: 0

In a number of real-world applications, there is a range of noise associated with individual data points. Some points are extracted under relatively clear and defined conditions, while others may be affected by a variety of known or unknown confounding factors, which may decrease those points' validity. These points may ...

8 published by ACM
September 2014 BCB '14: Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 5,   Downloads (12 Months): 33,   Downloads (Overall): 109

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This research employs an exhaustive search of different attribute selection algorithms in order to provide a more structured approach to learning design for prediction of Alzheimer's clinical dementia rating (CDR).
Keywords: CDR, Alzheimer's disease, ensemble machine learning

9
September 2014 MLAS'14: Proceedings of the 2014 International Conference on Meta-learning and Algorithm Selection - Volume 1201
Publisher: CEUR-WS.org
Bibliometrics:
Citation Count: 0

The success of machine learning on a given task depends on, among other things, which learning algorithm is selected and its associated hyperparameters. Selecting an appropriate learning algorithm and setting its hyperparameters for a given data set can be a challenging task, especially for users who are not experts in ...

10
September 2014 MLAS'14: Proceedings of the 2014 International Conference on Meta-learning and Algorithm Selection - Volume 1201
Publisher: CEUR-WS.org
Bibliometrics:
Citation Count: 0

Work on metalearning for algorithm selection has often been criticized because it mostly considers only the default parameter settings of the candidate base learning algorithms. Many have indeed argued that the choice of parameter values can have a significant impact on accuracy. Yet little empirical evidence exists to provide definitive ...

11
September 2014 MLAS'14: Proceedings of the 2014 International Conference on Meta-learning and Algorithm Selection - Volume 1201
Publisher: CEUR-WS.org
Bibliometrics:
Citation Count: 1

The results from most machine learning experiments are used for a specific purpose and then discarded. This causes significant loss of information and requires rerunning experiments to compare learning algorithms. Often, this also requires a researcher or practitioner to implement another algorithm for comparison, that may not always be correctly ...

12 published by ACM
August 2014 ACM Transactions on Knowledge Discovery from Data (TKDD): Volume 8 Issue 4, October 2014
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 7,   Downloads (12 Months): 26,   Downloads (Overall): 378

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We examine the problem of identifying social circles, or sets of cohesive and mutually aware nodes surrounding an initial query set, in directed graphs where the complete graph is not known beforehand. This problem differs from local community mining, in that the query set defines the circle of interest. We ...
Keywords: local community search, Social circles, directed graphs

13
July 2014 Data Mining and Knowledge Discovery: Volume 28 Issue 4, July 2014
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 14

A number of studies, theoretical, empirical, or both, have been conducted to provide insight into the properties and behavior of interestingness measures for association rule mining. While each has value in its own right, most are either limited in scope or, more importantly, ignore the purpose for which interestingness measures ...
Keywords: Association rule mining, Interestingness measures, Behavior analysis, Clustering

14
May 2014 Intelligent Data Analysis: Volume 18 Issue 3, May 2014
Publisher: IOS Press
Bibliometrics:
Citation Count: 0

Traditional association rule mining algorithms often have difficulty handling questions that are implicitly related, producing rules that are very accurate but are so obvious as to be completely useless to researchers. This problem is compounded by the fact that standard objective measures for interestingness often capture the wrong information and ...
Keywords: Clustering, Association Rule Mining, Questionnaire Data

15
May 2014 Machine Learning: Volume 95 Issue 2, May 2014
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 10

Most data complexity studies have focused on characterizing the complexity of the entire data set and do not provide information about individual instances. Knowing which instances are misclassified and understanding why they are misclassified and how they contribute to data set complexity can improve the learning process and could guide ...
Keywords: Instance hardness, Data complexity, Dataset hardness

16
March 2014 Intelligent Data Analysis: Volume 18 Issue 2, March 2014
Publisher: IOS Press
Bibliometrics:
Citation Count: 0

We illustrate the danger of using default implementations of learning algorithms by showing that the implementation of RBF networks in the three most popular open source data mining software packages causes the algorithm to behave and perform like naïve Bayes in most instances. This result has significant implications for both ...
Keywords: Metalearning, NaïVe Bayes, Algorithm Analysis, Rbf Networks

17 published by ACM
August 2013 ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Publisher: ACM
Bibliometrics:
Citation Count: 1
Downloads (6 Weeks): 1,   Downloads (12 Months): 13,   Downloads (Overall): 135

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The explosion of online social media has increased people's ability to share content and link with others, thus allowing diverse communities to emerge naturally as a product of interaction among participants. Mothers have certainly not been foreign to this development. Many have embraced the new technology to share experiences, thoughts, ...

18
July 2013 Intelligent Data Analysis: Volume 17 Issue 4, July 2013
Publisher: IOS Press
Bibliometrics:
Citation Count: 3

Classification algorithm selection is an open research problem whose solution has tremendous value for practitioners. In recent years, metalearning has emerged as a viable approach. Unfortunately, the ratio of examples to classes is small at the metalevel for any reasonable number of algorithms to choose from, and there are serious ...
Keywords: Algorithm Selection, Clustering, Metalearningg

19
June 2013 Computers in Biology and Medicine: Volume 43 Issue 5, June, 2013
Publisher: Pergamon Press, Inc.
Bibliometrics:
Citation Count: 1

The National Health and Nutrition Examination Survey (NHANES), administered annually by the National Center for Health Statistics, is designed to assess the general health and nutritional status of adults and children in the United States. Given to several thousands of individuals, the extent of this survey is very broad, covering ...
Keywords: Evidence-based medicine, Medical data mining, NHANES, Observational study

20
December 2012 SocInfo'12: Proceedings of the 4th international conference on Social Informatics
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 0

This paper describes how a nascent collective of individuals can coalesce into a complex social system. The systematic study of such scenarios requires a mathematical framework within which to model the behavior of the individual members of the collective. As individuals interact, they develop social relationships and exchange resources --- ...



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