2 Search Results for "Ramakrishnan, Raghu"


Document
Parallel Data Analysis (Dagstuhl Seminar 13251)

Authors: Artur Andrzejak, Joachim Giesen, Raghu Ramakrishnan, and Ion Stoica

Published in: Dagstuhl Reports, Volume 3, Issue 6 (2013)


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 13251 "Parallel Data Analysis" which was held in Schloss Dagstuhl - Leibniz Center for Informatics from June 16th 2013 to June 21st 2013. During the seminar, participants presented their current research and ongoing work, and open problems were discussed. The first part of this document describes seminar goals and topics, while the remainder gives an overview of the contents discussed during this event. Abstracts of a subset of the presentations given during the seminar are put together in this paper. Links to extended abstracts or full papers are provided, if available.

Cite as

Artur Andrzejak, Joachim Giesen, Raghu Ramakrishnan, and Ion Stoica. Parallel Data Analysis (Dagstuhl Seminar 13251). In Dagstuhl Reports, Volume 3, Issue 6, pp. 67-82, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)


Copy BibTex To Clipboard

@Article{andrzejak_et_al:DagRep.3.6.67,
  author =	{Andrzejak, Artur and Giesen, Joachim and Ramakrishnan, Raghu and Stoica, Ion},
  title =	{{Parallel Data Analysis (Dagstuhl Seminar 13251)}},
  pages =	{67--82},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2013},
  volume =	{3},
  number =	{6},
  editor =	{Andrzejak, Artur and Giesen, Joachim and Ramakrishnan, Raghu and Stoica, Ion},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.3.6.67},
  URN =		{urn:nbn:de:0030-drops-42580},
  doi =		{10.4230/DagRep.3.6.67},
  annote =	{Keywords: data analysis, machine learning, parallel processing, distributed computing, software frameworks}
}
Document
Data Mining: The Next Generation

Authors: Raghu Ramakrishnan, Rakesh Agrawal, Johann-Christoph Freytag, Toni Bollinger, Christopher W. Clifton, Saso Dzeroski, Jochen Hipp, Daniel Keim, Stefan Kramer, Hans-Peter Kriegel, Ulf Leser, Bing Liu, Heikki Mannila, Rosa Meo, Shinichi Morishita, Raymond Ng, Jian Pei, Prabhakar Raghavan, Myra Spiliopoulou, Jaideep Srivastava, and Vicenc Torra

Published in: Dagstuhl Seminar Proceedings, Volume 4292, Perspectives Workshop: Data Mining: The Next Generation (2005)


Abstract
Data Mining (DM) has enjoyed great popularity in recent years, with advances in both research and commercialization. The first generation of DM research and development has yielded several commercially available systems, both stand-alone and integrated with database systems; produced scalable versions of algorithms for many classical DM problems; and introduced novel pattern discovery problems. In recent years, research has tended to be fragmented into several distinct pockets without a comprehensive framework. Researchers have continued to work largely within the parameters of their parent disciplines, building upon existing and distinct research methodologies. Even when they address a common problem (for example, how to cluster a dataset) they apply different techniques, different perspectives on what the important issues are, and different evaluation criteria. While different approaches can be complementary, and such a diversity is ultimately a strength of the field, better communication across disciplines is required if DM is to forge a distinct identity with a core set of principles, perspectives, and challenges that differentiate it from each of the parent disciplines. Further, while the amount and complexity of data continues to grow rapidly, and the task of distilling useful insight continues to be central, serious concerns have emerged about social implications of DM. Addressing these concerns will require advances in our theoretical understanding of the principles that underlie DM algorithms, as well as an integrated approach to security and privacy in all phases of data management and analysis. Researchers from a variety of backgrounds assembled at Dagstuhl to re-assess the current directions of the field, to identify critical problems that require attention, and to discuss ways to increase the flow of ideas across the different disciplines that DM has brought together. The workshop did not seek to draw up an agenda for the field of DM. Rather, it offers the participants’ perspective on two technical directions – compositionality and privacy – and describes some important application challenges that drove the discussion. Both of these directions illustrate the opportunities for crossdisciplinary research, and there was broad agreement that they represent important and timely areas for further work; of course, the choice of these directions as topics for discussion also reflects the personal interests and biases of the workshop participants.

Cite as

Raghu Ramakrishnan, Rakesh Agrawal, Johann-Christoph Freytag, Toni Bollinger, Christopher W. Clifton, Saso Dzeroski, Jochen Hipp, Daniel Keim, Stefan Kramer, Hans-Peter Kriegel, Ulf Leser, Bing Liu, Heikki Mannila, Rosa Meo, Shinichi Morishita, Raymond Ng, Jian Pei, Prabhakar Raghavan, Myra Spiliopoulou, Jaideep Srivastava, and Vicenc Torra. Data Mining: The Next Generation. In Perspectives Workshop: Data Mining: The Next Generation. Dagstuhl Seminar Proceedings, Volume 4292, pp. 1-33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)


Copy BibTex To Clipboard

@InProceedings{ramakrishnan_et_al:DagSemProc.04292.1,
  author =	{Ramakrishnan, Raghu and Agrawal, Rakesh and Freytag, Johann-Christoph and Bollinger, Toni and Clifton, Christopher W. and Dzeroski, Saso and Hipp, Jochen and Keim, Daniel and Kramer, Stefan and Kriegel, Hans-Peter and Leser, Ulf and Liu, Bing and Mannila, Heikki and Meo, Rosa and Morishita, Shinichi and Ng, Raymond and Pei, Jian and Raghavan, Prabhakar and Spiliopoulou, Myra and Srivastava, Jaideep and Torra, Vicenc},
  title =	{{Data Mining: The Next Generation}},
  booktitle =	{Perspectives Workshop: Data Mining: The Next Generation},
  pages =	{1--33},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4292},
  editor =	{Rakesh Agrawal and Johann Christoph Freytag and Raghu Ramakrishnan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.04292.1},
  URN =		{urn:nbn:de:0030-drops-2709},
  doi =		{10.4230/DagSemProc.04292.1},
  annote =	{Keywords: Data mining, databases, artificial intelligence, machine learning, statistics, semantics}
}
  • Refine by Author
  • 2 Ramakrishnan, Raghu
  • 1 Agrawal, Rakesh
  • 1 Andrzejak, Artur
  • 1 Bollinger, Toni
  • 1 Clifton, Christopher W.
  • Show More...

  • Refine by Classification

  • Refine by Keyword
  • 2 machine learning
  • 1 Data mining
  • 1 artificial intelligence
  • 1 data analysis
  • 1 databases
  • Show More...

  • Refine by Type
  • 2 document

  • Refine by Publication Year
  • 1 2005
  • 1 2013

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail