Meetings/Workshops on Information & Knowledge Management, Big Data Computing in the United States (USA)

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SnowPAC 2018 — Big Questions, Big Surveys, Big Data: Nighttime Astronomy and Cosmology in the 2020s
11 Mar 2018 • Snowbird, Utah, United States
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SDM — SIAM International Conference on Data Mining
03 May 2018 - 05 May 2018 • San Diego, United States
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JCDL — International ACM/IEEE Joint Conference on Digital Libraries
03 Jun 2018 - 07 Jun 2018 • Fort Worth, United States
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SIGMOD — ACM SIGMOD International Conference on Management of Data
10 Jun 2018 - 15 Jun 2018 • Houston, United States
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Big Data Summer Institute
17 Jun 2018 - 27 Jul 2018 • University of Michigan School of Public Health, An, United States
This full-time 6-week summer institute will introduce undergraduate students to emerging challenges at the intersection of Big Data, Statistics, and Human Health. Lectures will be led by a diverse group of stellar biostatistics, statistics, electrical engineering, and computer science faculty at the University of Michigan. Working in teams, students will participate in mentored big data research projects. Full and partial stipends are available for selected applicants based on merit and need.
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SIGIR — ACM SIGIR Conference on Research and development in information retrieval
08 Jul 2018 - 12 Jul 2018 • Ann Arbor Michigan, United States
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ICDM — IEEE International Conference on Data Mining
11 Jul 2018 - 15 Jul 2018 • New York, United States
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TrustCom/BigDataSE — 2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering
01 Aug 2018 - 03 Aug 2018 • New York, NY, United States
The conference aims at bringing together researchers and practitioners in the world working on trusted computing and communications, with regard to trust, security, privacy, reliability, dependability, survivability, availability, and fault tolerance aspects of computer systems and networks, and providing a forum to present and discuss emerging ideas and trends in this highly challenging research field
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Science at Extreme Scales: Where Big Data Meets Large-Scale Computing
12 Sep 2018 - 14 Dec 2018 • Institute for Pure and Applied Mathematics (IPAM),, United States
The breathtaking progress in both computer technologies and advanced methods to effectively and efficiently exploit them opens the door for a completely "new kind of science" at the beginning of the 21st century. This paradigm change has been brought about by two waves of innovations. The first wave primarily focused on High Performance Computing (HPC). Simulations and optimizations enable breakthroughs in the fundamental understanding or improvement of processes and systems in various domains of science and engineering. The second wave, which started later, aims at the comprehensive modeling of natural science, engineering, and societal phenomena in a data-driven way, with an even broader impact, also reaching the social sciences and humanities. Data sets from observations, experiments, simulations, imaging, digitization, or social networks as well as business or patient data are collected, processed, and analyzed.
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Science at Extreme Scales: Where Big Data Meets Large-Scale Computing Tutorials
13 Sep 2018 - 18 Sep 2018 • Institute for Pure and Applied Mathematics (IPAM),, United States
The program opens with four days of tutorials that will provide an introduction to major themes of the entire program and the four workshops. The goal is to build a foundation for the participants of this program who have diverse scientific backgrounds. The themes will cover topics in computer science, big data analysis, machine learning, and numerical analysis.
Part of the Long Program Science at Extreme Scales: Where Big Data Meets Large-Scale Computing
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Big Data Meets Large-Scale Computing
24 Sep 2018 - 28 Sep 2018 • Institute for Pure and Applied Mathematics (IPAM),, United States
Large data sets are increasingly being ingested (e.g., in data assimilation) and produced (e.g., in uncertainty quantification) by traditional simulations. Important questions that emerge are: What experience from traditional simulations is transferable to newly emerging big data applications? Conversely, what new optimal algorithms will emerge that are motivated by data intensive applications being pushed to large scales? How will they enrich traditional simulations? Examples of topics that will be discussed: 1)requirements and relations of high-performance analytics and simulation; (2) scalable hierarchical algorithms for analytics and simulation; (3)detecting and exploiting data sparsity within large-scale data sets; and (4)open problems, where no scalable methods yet exist. This workshop will bring together analysts and developers of computationally and data intensive applications interested in early exploitation of extreme scale computing platforms.
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Workshop II: HPC-driven Applications Go Big Data
15 Oct 2018 - 19 Oct 2018 • Institute for Pure and Applied Mathematics (IPAM),, United States
Classical HPC applications-usually based on numerically solving sets of ODEs or PDEs-develop towards a data-centric approach. This includes patient-specific simulations in medicine, integrated analytics of experimental and simulation data in plasma physics, learning from simulation data, and many more. We will discuss the question: What are the implications, needs, opportunities, and limitations in this context?
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KR — Principles of Knowledge Representation and Reasoning
30 Oct 2018 - 02 Nov 2018 • Tempe, United States
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AIP Conference Proceedings
Last updated: 22 December 2017