New! Carlos Guestrin NIPS Big Learning Workshop talk:

GraphLab papers

• Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin and J. Hellerstein. GraphLab: A New Framework for Parallel Machine Learning. In the 26th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, USA, 2010. arxiv presentation
• Technical report describing the GraphLab abstraction is here.
• Technical report with performance comparison vs. Mahout/hadoop and MPI: arxiv.
• Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin, J. Hellerstein, Distributed GraphLab: A Framework for Machine Learning in the Cloud, in VLDB 2012, to appear.

Papers that cite GraphLab as a viable parallel computation platform

• Stephen Boyd , Neal Parikh , Eric Chu, Borja Peleato and Jonathan Eckstein. Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers.To appear in Foundations and Trends in Machine Learning, Michael Jordan, Editor in Chief. Original draft version posted November 2010. html
• Tuyen N. Huynh. Improving the Accuracy and Scalability of Discriminative Learning Methods for Markov Logic Networks. PhD Thesis, Department of Computer Science, University of Texas at Austin, May 2011. 159 pages. pdf

Papers that use GraphLab for implementing applications

• L. Song, A. Gretton, D. Bickson, Y. Low and C. Guestrin. Kernel Belief Propagation. In the 14th International Conference on Artificial Intelligence and Statistics (AISTATS) 2011. arxiv
• D. Bickson and C. Guestrin. Inference with multivariate heavy-tails in linear models. In Neural Information Processing Systems (NIPS) 2010, Vancouver, Canada, Dec. 2010. arxiv
• Joseph Gonzalez, Yucheng Low, Arthur Gretton, Carlos Guestrin (2011). "Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees. pdf

Notable presentations

• D. Bickson. Large scale iterative computation using GraphLab. In Hungarian National Academy of Science, Budapest 3/22/12.
• J. Gonzalez. Big Learning with Graphs. Lecture in Machine Learning with Large Datasets. CMU. 3/8/12. [PPTX]
• D. Bickson. Large scale iterative computation using GraphLab. Gatsby Computational Neuroscience Unit, UCL London 2/15/12.
• C. Guestrin. NIPS Big Learning Workshop 12/18/2011. [PPTX]
• D. Bickson. Large scale iterative computation using GraphLab. Ohio State University 11/3/2011.
• J. Gonzalez. GraphLab talk at the IDGA Data Center Conslidation Summit. [PPTX] 10/3/2011
• J. Gonzalez. Early GraphLab 2 Talk at Yahoo! Research. [PPTX] 9/9/2011
• J. Gonzalez. GraphLab talk at Berkeley. [PPTX] 9/7/2011
• J. Gonzalez. GraphLab talk at Greenplum EMC. [PPTX] 8/24/2011
• J. Gonzalez. GraphLab talk at LinkedIn. [PPTX] 8/2/2011
• J. Gonzalez. GraphLab talk at Cloudera. [PPTX] 7/29/2011
• J. Gonzalez. GraphLab talk at Facebook. [PPTX] 7/19/2011
• D. Bickson. Large scale iterative computation using GraphLab. Yahoo! Research NY. 5/17/2011.
• D. Bickson. Parallel Machine Learning using GraphLab. geekSessions 2.1: Data Scalability SQL or NoSQL? San Fransisco. CA. website. 5/3/2011.
• Y. Low. GraphLab: A Distributed Framework for Machine Learning TeraGrid, Blue Waters sponsor Symposium on Data-Intensive Analysis, Pittsburgh Supercomputing center. 4/14/2011
• C. Guestrin Keynote: Machine Learning in the Cloud with GraphLab. LCCC : NIPS 2010 Workshop on Learning on Cores, Clusters and Clouds. lecture video and slides. 12/11/2010
• D. Bickson. GraphLab: a new framework for parallel machine learning. Army research office MURI annual meetings, Salt Lake City. 8/19/2010
• Y. Low. GraphLab: A New Framework for Parallel Machine Learning. The 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010). 7/11/2010