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Joseph Gonzalez

Joseph Gonzalez
Postdoc, UC Berkeley

Website | @mejoeyg

I am a postdoc in the AMPLab at UC Berkeley where I am continuing work on large-scale systems for machine learning as well as the GraphLab project. As a graduate student I worked with Carlos Guestrin in the Machine Learning Department at Carnegie Mellon University (CMU). My research addresses the challenges of designing and building large-scale machine learning algorithms and systems. In particular, my thesis focuses on large-scale structured machine learning using probabilistic graphical models that are capable of reasoning about billions of related random variables. The resulting algorithms and systems have achieved state-of-the-art performance in tasks ranging from predicting ad preferences in social networks to solving complex protein modeling tasks. As part of my thesis work we created GraphLab , a framework that dramatically simplifies the design and implementation of high-performance large-scale machine learning systems.


Hadoop & Beyond Murray Hill Suite
Carlos Guestrin (Apple | University of Washington ), Joseph Gonzalez (UC Berkeley)
Average rating: ****.
(4.86, 7 ratings)
GraphLab is like Hadoop for graphs. Users express graph processing algorithms using a simple API and the GraphLab runtime efficiently executes that computation on multicore and distributed architectures. By leveraging advances in graph representation, asynchronous communication, and scheduling, GraphLab is able to achieve orders-of-magnitude performance gains over existing systems like Hadoop. Read more.


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