Agenda
| Time | Session | Talk title (and length) | Speaker |
|---|---|---|---|
| 08:00 – 09:00 | Reception | Reception and continental breakfast | |
| 09:00 – 10:30 | Morning session | GraphLab Version 2 Overview (60 mins) | Carlos Guestrin |
| Large scale ML challenges | Ted Willke, Intel Labs | ||
| 10:30 – 10:50 | Break | ||
| 10:50 – 12:20 | Late morning session | Bloom: Disorderly Programming for Distributed Systems (30 mins) | Joseph Hellerstein, UC Berkeley |
| Schism: Graph Partitioning for Scalable Query Processing on Large OLTP Databases | Sam Madden – MIT | ||
| Visualization and Interactive Data Analysis | Jeffrey Heer, Stanford | ||
| 12:20 – 13:50 | Lunch Break | ||
| 13:40 – 14:55 | Afternoon session | The ParameterServrer | Alexander Smola, Yahoo! Labs |
| Vowpal Wabbit for Extremely Fast Machine Learning | Lihong Li, Yahoo! Research | ||
| Cassovary Graph Processing System | Pankaj Gupta, Twitter | ||
| Tera Scale Deep Learning | Quoc Le, Stanford & Google | ||
| 14:55 – 15:15 | Break | ||
| 15:15 – 17:10 | Late afternoon session | Identifying densely overlapping clusters in large networks | Jure Leskovec, Stanford |
| Large-scale Single-pass k-Means Clustering at Scale | Ted Dunning, MapR Technologies | ||
| Recommendations @Netflix: Big Data, Smart Models & Scalable Systems | Xavier Amatriain - Netflix | ||
| Large scale ML at Pandora | Tao Ye, Pandora Internet Radio | ||
| NIMBLE - A toolkit for the implementation of parallel data mining and machine learning algorithms on Map-Reduce (15 mins) | Amol Ghoting, IBM Watson (presented by: Prabhanjan Kambadur) | ||
| Machine learning in One Kings Lane (5 mins) | Mohit Singh, One Kings Lane | ||
| 17:10 – 19:00 | Poster/demo session | See detailed list below | Instructions for presenters |
Posters/Demos (GraphLab Workshop 2012 Posters)
- GraphBuilder - Large-Scale Graph Construction using Apache™ Hadoop™ : Nilesh Jain, Diana Hu, Jay Gu, Frank Berry, Intel Labs
- Green Marl graph processing framework – Sungpack Hong, Oracle Labs
- Machine learning benchmark framework – Nicholas Kolegraff, Accenture
- Skytree Server: Enterprise-grade Scalable Machine Learning – Alex Gray, Georgia Tech
- Alpine and MADLib Demo – Steven Hilion, Alpine Data Labs
- Disk-based Massive Graph Computation – Aapo Kyrola, CMU
- Titan: A Highly Scalable, Distributed Graph Database - Matthias Broecheler, Aurelius
- Distributed Active Graph Platform, Andrey Logvinov, Meralabs LLC
- Health Insights in Real-Time. Adam Sadilek, Andrew Abumoussa, Sean Brennan, Henry Kautz University of Rochester
- YarcData graph analytics contest, Monte LaBute, YarcData
- Grappa: faster graph processing on mass-market clusters, Jacob Nelson, University of Washington
- Giraph: Large-scale graph processing infrastructure on Hadoop, Avery Ching, Facebook
[...] GraphLab Workshop Presentations [...]
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