Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

November 4, 2013

The 3rd GraphLab Conference is coming!

Filed under: GraphLab,Graphs — Patrick Durusau @ 10:16 pm

The 3rd GraphLab Conference is coming! by Danny Bickson.

From the post:

We have just started to organize our 3rd user conference on Monday July 21 in SF. This is a very preliminary notice to attract companies and universities who like to be involved. We are planning a mega event this year with around 800-900 data scientists attending, with the topic of graph analytics and large scale machine learning.

The conference is a non-profit event held by GraphLab.org to promote applications of large scale graph analytics in industry. We invite talks from all major state-of-the-art solutions for graph processing, graph databases and large scale data analytics and machine learning. We are looking for sponsors who would like to contribute to the event organization.

The best recommendation I can make for the 3rd GraphLab Conference is to point to the videos from the 2nd GraphLab Conference.

There you will find videos and slides for:

  • Molham Aref, LogicBlox – Datalog as a foundation for probabilistic programming
  • Dr. Avery Ching, Facebook – Graph Processing at Facebook Scale
  • Prof. Carlos Guestrin, GraphLab Inc. & University of Washington: Graphs at Scale with GraphLab
  • Dr. Pankaj Gupta, Twitter – WTF: The Who to Follow Service at Twitter
  • Prof. Joe Hellerstein – Professor, UC Berkeley and Co-Founder/CEO, Trifacta – Productivity for Data Analysts: Visualization, Intelligence and Scale
  • Aapo Kyrola, CMU – What can you do with GraphChi – what’s new?
  • Prof. Michael Mahoney, Stanford – Randomized regression in parallel and distributed environments
  • Prof. Vahab Mirrokni, Google – Large-scale Graph Clustering in MapReduce and Beyond
  • Dr. Derek Murray , Microsoft Research- Incremental, iterative and interactive data analysis with Naiad
  • Prof. Mark Oskin, University of Washington, Grappa graph engine.
  • Dr. Lei Tang – Walmart Labs – Adaptive User Segmentation for Recommendation
  • Prof. S V N Vishwanathan, PurdueNOMAD: Non-locking stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix factorization
  • Dr. Theodore Willke, Intel LabsIntel GraphBuilder 2.0

Spread the word!

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