Speakers

Carlos Guestrin

Prof. Carlos Guestrin, GraphLab Inc. & University of Washington

Joe Hellerstein

Prof. Joe Hellerstein, Professor, UC Berkeley and Co-Founder/CEO, Trifacta

Productivity for Data Analysts: Visualization, Intelligence and Scale

Mark Oskin

Prof. Mark Oskin, University of Washington

Grappa graph engine

Ralf Herbrich

Dr. Ralf Herbrich, Amazon

The Sum-Product Algorithm for Factor Graphs Revisited

Christopher Re

Prof. Christopher Re, University of Wisconsin-Madison

Ted Willke

Dr. Theodore Willke, Intel Labs

Intel GraphBuilder 2.0

Avery Ching

Dr. Avery Ching, Facebook

Graph Processing at Facebook Scale

Vahab Mirrokni

Prof. Vahab Mirrokni, Google

Clustering and Connected Components in Mapreduce and Beyond

Derek Murry

Dr. Derek Murray

Incremental, iterative and interactive data analysis with Naiad

Pankaj Gupta

Dr. Pankaj Gupta, Twitter

WTF: The Who to Follow Service at Twitter

Lei Tang

Dr. Lei Tang, Walmart Labs

Adaptive User Segmentation for Recommendation

Michael Mahoney

Prof. Michael Mahoney, Stanford

Distributed Regression

Molham Aref

Molham Aref, LogicBlox

Datalog as a foundation for probabilistic programming

Steve Hillion

Dr. Steven Hillion, Alpine Data Labs

General implementation methods for machine-learning algorithms on billions of rows and millions of features

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, Berkeley: 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

Sponsors

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