TECH TALK: “In-Memory Data Mining via Succinct Data Structures”
ABSTRACT: “We often use “Big Data” techniques when most users only have “big data”. “Big data” can often be handled efficiently by applying standard algorithms developed, tried and tested but coupled with succinct data structures to reduce the memory usage of such algorithms, thus allowing the “big data” to be processed in memory. I will introduce some recent applications to mining “big data”.
Rajeed Raman is Professor of Computer Science, at the Department of Informatics, in the University of Leicester, United Kingdom. His research interests are broadly in algorithms and complexity and mostly lie in the area of data structure design. In recent years he has worked in succinct data structures. SDS represent user-provided data using an amount of computer memory close to the information-theoretic minimum and support very rapid queries and updates on the data. SDS have been shown to have a very good theoretical and practical performance for a growing range of applications including text search and XML processing. In addition to studying algorithms from a mathematical viewpoint, Prof, Raman is actively involved in algorithm engineering, including the implementation, experimental testing, and fine-tuning of discrete algorithms; the development of software repositories and platforms which allow the use of, and experimentation with, efficient discrete algorithms; methodological issues including standards in the context of empirical research on algorithms and data structures; methodological issues regarding the process of converting user requirements into efficient algorithmic solutions and implementations. Prof. Raman is also interested in data mining and he is a member of an active working group on Knowledge Discovery and Machine Learning. His interests are mining of uncertain data and applications of succinct data structures to data mining.
WHERE: Auditorio Ramón Picarte, DCC U. de Chile, Beauchef 851, Edificio Poniente, Tercer Piso. Santiago.
DATE/TIME: Lunes 29 de abril de 2019, de 11.00 a 12.00 horas.
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