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  • Big Learning : Algorithms, Systems, and Tools

Big Learning : Algorithms, Systems, and Tools

TechTalks from event: Big Learning : Algorithms, Systems, and Tools

  • Stochastic Variational Inference Authors: David M. Blei
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  • Parallel Markov Chain Monte Carlo for Dirichlet Process Mixture Models or ClusterCluster: How I Learned to Stop Worrying and Love Latent Variables and MapReduce Authors: Dan Lovell, Ryan Adams, Vikash Mansinghka
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  • Streaming Balanced Graph Partitioning for Random Graphs Authors: Isabelle Stanton
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  • Conditional Gradient Algorithms for Large-Scale Learning Authors: Zaid Harchaoui, A. Juditsky, A. Nemirovski
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  • Temporal Analytics on Big Data for Web Advertising and a Grand ML/DB Challenge Authors: Jonathan Goldstein, Bardish Chandramouli, Songyun Duan
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  • Statistical Inference for Big Data Problems in Molecular Biophysics Authors: Arvind Ramanathan, Andrei J. Saval, Virginia M. Burger, Shannon Quinn, Pratul K. Agarwal, Chakra S. Chennubhotia
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  • Randomized Sampling in Exploration Seismology Authors: Felix J. Herrmann, SLIM Team, Eldad Haber, Michael Friendlander
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  • All Talks
    • Stochastic Variational Inference
    • Parallel Markov Chain Monte Carlo for Dirichlet Process Mixture Models or ClusterCluster: How I Learned to Stop Worrying and Love Latent Variables and MapReduce
    • Streaming Balanced Graph Partitioning for Random Graphs
    • Conditional Gradient Algorithms for Large-Scale Learning
    • Temporal Analytics on Big Data for Web Advertising and a Grand ML/DB Challenge
    • Statistical Inference for Big Data Problems in Molecular Biophysics
    • Randomized Sampling in Exploration Seismology

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  • About:Big Learning : Algorithms, Systems, and Tools
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