GraphLab 2012

08:00 – 09:00 Registration and reception
09:00 – 10:00 Prof. Carlos Guestrin, GraphLab Inc. & University of Washington:
10:00 – 10:30 Prof. Joe Hellerstein – Professor, UC Berkeley and Co-Founder/CEO, Trifacta – Productivity for Data Analysts: Visualization, Intelligence and Scale
10:30 – 11:00 Prof. Mark Oskin, University of Washington, Grappa graph engine.
11:00-11:20 Coffee Break
11:20 – 11:50 Dr. Ralf Herbrich, Amazon – The Sum-Product Algorithm for Factor Graphs Revisited
11:50 – 12:20 Prof. Christopher Re, University of Wisconsin-Madison – TBA
12:20 – 13:50 Lunch break (on your own)
13:50 – 14:10 Ted Willke MLconf Dr. Theodore Willke, Intel Labs – Intel GraphBuilder 2.0
14:10 – 14:30 avery ching Dr. Avery Ching, Facebook – Graph Processing at Facebook Scale
14:30 – 14:50 Prof. Vahab Mirrokni, Google – Clustering and Connected Components in Mapreduce and Beyond
14:50 – 15:10 Dr. Derek Murray – Incremental, iterative and interactive data analysis with Naiad
15:10 – 15:30 Coffee Break
15:30 – 15:50 pankaj gupta Dr. Pankaj Gupta, Twitter – WTF: The Who to Follow Service at Twitter
15:50 – 16:10 Dr. Lei Tang – Walmart Labs – Adaptive User Segmentation for Recommendation
16:10 – 16:30 Prof. Michael Mahoney, Stanford – Distributed Regression
16:30 – 16:50 Molham aref Molham Aref, LogicBlox – Datalog as a foundation for probabilistic programming
16:50 – 17:10 Dr. Steven Hillion, Alpine Data Labs – General implementation methods for machine-learning algorithms on billions of rows and millions of features
17:10 – 19:00 Poster & Demo session Posters:

  • Joshua Vogelstein, Duke – Optimal Subspace Projection for High-Dimensional Classification and Testing.
  • Aydin Buluc, LNL – Parallel software for high-performance and high-productivity graph analysis.
  • Brian Thompson, Systap – GAS Engine for the GPU.
  • Norbert Martínez, Andrey Gubichev , Alex Averbuch, LDBC -Linked Data Benchmark Council – an initiative to standardize graph systems benchmarking
  • Norbert Martínez Sparsity technologies DEX: a High-Performance Graph Database Management System
  • Aapo Kyrola, CMU – What’s new in GraphChi?
  • Valeria Nikolaenko ,Stanford – Privacy-Preserving Ridge Regression on Hundreds of Millions of Records
  • Ameet Talwalkar, Bekereley – MLBase
  • George Ng, YarcData – YarcData:  Enabling discovery at speed and scale.
  • Radhika Tekkath, Agivox – A Deeper Dive into Understanding User Interest in News and Blogs

Demos:

  • Joseph Gonzalez & Reynold Xin, Berekeley AMP Lab – GraphX: Interactive Graph Mining
  • Shivaram Venkataraman & Kyungyong Lee Bekereley/HP Labs – Presto: Distributed Machine Learning and Graph Processing with Sparse Matrices
  • Ely Kahn, Sqrrl – Scalable graph storage and analysis using Sqrrl Enterprise
  • Jans Aasman, Allgero Graph -Exploring and discovering new patterns in graphs using Gruff and AllegroGraph
  • Jan Neumann, Comcast-  Personalized Recommendations at Comcast
  • Murat Can, CMU – repurpose drugs by running collaborative filtering algorithms on pharmacological datasets
  • Tim Wilson, smarttypes.org – The map equation: using information theory to analyze your markov transition matrix
  • Matthias Broecheler,   Aurelius –   The Aurelius Graph Cluster – Graph Computing at Scale
  • Jason Riedy, USF – STING: High-Performance Analysis for Streaming, Graph-Structured Data

Click to see our impressing list of demos and program committee.

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