NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Machine Learning...
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Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Machine Learning and Hadoop by Josh Wills Abstract: We'll review common use cases for machine learning and advanced analytics found in our customer base at Cloudera and ways in which Apache Hadoop supports these use cases. We'll then discuss... Read more
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Machine Learning...
February 28, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Machine Learning and Hadoop by Josh Wills Abstract: We'll review common use cases for machine learning and advanced analytics found in our customer base at Cloudera and ways in which Apache H...
0 people like this
- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Randomized Smoothing for...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Randomized Smoothing for (Parallel) Stochastic Optimization by John Duchi John Duchi is currently a PhD candidate in computer science at Berkeley, where he started in the fall of 2008. He wor...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Large-Scale Matrix...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent by Rainer Gemulla Rainer Gemulla graduated from the Technische Universität Dresden in Germany in the area of data...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Graphlab 2 Tutorial
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Tutorial: GraphLab 2.0 by Yucheng Low Yucheng Low is a third year Phd student in the Machine Learning Department at Carnegie Mellon University advised by Carlos Guestrin. His current work is on abstractions...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Graphlab 2...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Graphlab 2: The Challenges of Large Scale Computation on Natural Graphs by Carlos Guestrin Carlos Guestrin is an Assistant Professor at Carnegie Mellon's Computer Science and Machine Learning ...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: No-U-Turn Sampler...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo by Matt Hoffman Matt Hoffman is a postdoc working with Prof. Andrew Gelman at Columbia University. His did his...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Block splitting for...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Block splitting for Large-Scale Distributed Learning by Neal Parikh Neal Parikh is a Ph.D. Candidate in the Department of Computer Science at Stanford University. Abstract: Machine learning ...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Hazy - Making Data-driven...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Hazy: Making Data-driven Statistical Applications Easier to build and Maintain by Chris Re Christopher (Chris) Ré is currently an assistant professor in the department of Computer Sciences at ...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Real time data...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Real time data sketches by Alex Smola Alex is a Principal Researcher at Yahoo. Alex's current research focus is on nonparametric methods for estimation, in particular kernel methods and expone...
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- -: NIPS 2011 Big Learning - Algorithms, Systems, & Tools Workshop: Spark: In-Memory Cluster...
February 14, 2012 (about 12 years ago)Big Learning Workshop: Algorithms, Systems, and Tools for Learning at Scale at NIPS 2011 Invited Talk: Spark: In-Memory Cluster Computing for Iterative and Interactive Applications by Matei Zaharia Matei Zaharia is a fifth year graduate student at UC Berkeley, working with Scott Shenker and Ion...
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