Konferenzen zum Thema Informations & Wissensmanagement, Big Data Computing in Singapur

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1
PAKDD — Pacific-Asia Conference on Knowledge Discovery and Data Mining
11. Mai 2020 - 14. Mai 2020 • Singapore, Singapur
Eintrags-ID:
1249685
2
Causal Inference with Big Data
29. Jun 2020 - 10. Jul 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
Causal inference is the study of quantifying whether a treatment, policy, or an intervention, denoted as A, has a causal effect on an outcome interest, denoted as Y. What distinguishes a causal effect of A on Y from an associative effect of A on Y, say by computing the correlation between A and Y, is that under a causal effect, intervening on the treatment A leads to changes in the outcome Y. Hence, a causal effect is a stronger notion of a relationship between A and Y than an associative effect.
Eintrags-ID:
1240642
3
Data Stream Algorithms
13. Jul 2020 - 21. Jul 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
The more data we have, the more data we need to process. Whether it is internet traffic or biological data, the hardware is never fast enough. The aim of this workshop is to focus on analysing data under new models: when the data cannot be stored (e.g., identifying viruses in the Internet traffic), when we use multiple cores to analyse the data, and when we are generating short sketches of the data to be sent and analysed by someone else. We believe a new set of algorithmic techniques (which rely mostly on statistics and on data structures) can be used in these models, and wish to find such techniques and employ them. An important focus of this workshop is to find algorithms which are elegant, and thus can also be used in practice. To develop these algorithms, it is critical to connect the key subareas of algorithmic research on big data. These key subareas include streaming, sketching, and sampling. The goal of the workshop is to bring researchers together from these different sub-areas and to establish strong collaborations among the attendees.
Eintrags-ID:
1240674
Verwandte Fachgebiete:
4
Optimization in the Big Data Era
03. Aug 2020 - 28. Aug 2020 • Singapore, Singapur
Veranstalter:
Institute for Mathematical Sciences/National University of Singapore
Zusammenfassung:
The field of optimization has undergone tremendous growth in its applications in science, engineering, business and finance in the past few decades. The growth has accelerated in recent years with the advent of big data analytics where optimization forms the core engine for solving and analyzing the underlying models and problems of extracting meaningful information from available data for the purpose of better decision making or getting better insights into the data sources. Spurred by the application needs and motivated by new emerging models in machine learning and data analytics, optimization research (in theory and algorithms) has also undergone rapid transformation and progress in recent years. In particular, demands for fast algorithms to solve extremely large-scale optimization problems arising from big data analytics have spurred numerous exciting new research directions in optimization theory and algorithms. The latter in turn helps to shape the development of optimization models and techniques in machine and statistical learning.
Eintrags-ID:
1240640


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Stand vom 18. Juli 2019