The GraphLab Big Learning Workshop is a meeting place for both academia and industry to discuss upcoming challenges of large scale machine learning and solution methods. The main goal for this year’s workshop is to bring together top researchers from academia, as well as top data scientists from industry with the special focus of large scale machine learning on sparse graphs.
We have secured talks and demos about the hottest graph processing systems including: GraphLab, Pregel (Google), Giraph (Facebook) , Cassovary (Twitter), Combinatorial BLAS (LBNL/UCSB), Allegro Graph (Franz) ,Neo4j, Titan (Aurelius), DEX (Sparsity Technologies), YarcData and others!
View the event pictures here »
Event Schedule:
8am – 9am: Registration, Coffee & Snacks
9am – Presentations begin (See list of speakers below)
5pm – 7pm Networking with hosted bar / appetizers
For updated agenda and detailed speaker info see the GraphLab Workshop site.
Confirmed Speakers for the GraphLab 2013 Workshop include:
- Prof. Carlos Guestrin, University of Washington – Graphlab 2.2 and Beyond
- Dr. Avery Ching, Facebook – Graph Processing at Facebook Scale
- Prof. Vahab Mirrokni, Google – Clustering and Connected Components in Mapreduce and Beyond
- 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
- Dr. Lei Tang – Walmart Labs – Adaptive User Segmentation for Recommendation
- Dr. Derek Murray – Incremental, iterative and interactive data analysis with Naiad
- Dr. Ralf Herbrich, Facebook – TBA
- Prof. Mark Oskin, University of Washington, Grappa graph engine.
Featured Projects
- Google’s Pregel is their Bulk Synchronous graph framework. Prof. Vahab Mirrokni is going to give an oral talk about graph processing @ Google.
- Apache Giraph is the open source equivalent system to Google’s Pregel. Dr. Avery Ching, one of Giraph contributors, will give a talk about large scale graph processing @ Facebook.
- Dr. Pankaj Gupta, the creator of Cassovary Graph Processing system @ Twitter will give a talk about Who To Follow (WTF) service in Twitter.
- Naiad is a parallel data flow framework from Microsoft with the focus of incremental computation. Dr. Derek Murray from Microsoft Research will present Naiad.
- GraphLab is CMU+UW open source graph processing system, which supports both bulk synchronous parallel as well as asynchronous computation. Prof. Carlos Guestrin will present the latest GraphLab project.
- Allegro Graph is a high performance graph database with RDF support. Jans Aasman, the CEO of Franz, will give a demo of their newest graph database.
- Combinatorial BLAS is a distributed memory parallel graph library from LBNL/UCSB. Dr. Aydin Buluc will present comb-BLAS.
- Grappa is a distributed graph processing framework using commodity processors, from The University of Washington. Prof. Mark Oskin will present Grappa.
- Titan is a distributed graph database. Dr. Matthias Broecheler will present Titan.
- Neo4j is an open source distributed graph database in Java. Alex Averbuch from neo4j will present neo4j.
- Infinite Graph from Objectivity is a distributed graph database.
- DEX is a high performance and scalable graph database system. Dr. Noerert Martinez will present DEX.
- YarcData, a Cray spinoff is creating customized hardware solutions for ultra fast graph processing.
- Systap LLC is a startup working on speeding up graph algorithms using GPUs. Bryan Thompson from Systap will present preliminary results of applying the gather apply scatter model on GPU.
Other notable talks at the GraphLab workshop:
- Trifacta is the hottest bay area startup out there, started by Prof. Joe Hellerstein from Berkeley and Prof. Jefferey Heer from Stanford. Prof. Joe Hellerstein will talk about Productivity for Data Analysts: Visualization, Intelligence and Scale.
- Dr. Lei Tang from Walmart Labs will talk about adaptive user segmentation for collaborative filtering.
- Alpine Data Labs is a Greenplum spinoff focusing on big data analytics. Seven Hillion will describe a case study of big data analytics on top of Hadoop.
