Playlist: 25 videos

Computational Challenges in Machine Learning

The aim of this workshop is to bring together a broad set of researchers looking at algorithmic questions that arise in machine learning. The primary target areas will be large-­scale learning, including algorithms for Bayesian estimation and...

1:5:29

Variational Inference: Foundations and Innovations

David Blei, Columbia University
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/david-blei-2017-5-1
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0:44:41

Representational and Optimization Properties of Deep Residual Networks

Peter Bartlett, UC Berkeley
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/tba-1
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0:41:36

Composing Graphical Models with Neural Networks for Structured Representations and Fast Inference

David Duvenaud, University of Toronto
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/david-duvenaud-2017-5-1
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0:46:48

Scaling Up Bayesian Inference for Big and Complex Data

David Dunson, Duke University
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/david-dunson-2017-5-1
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0:36:23

Unbiased Estimation of the Spectral Properties of Large Implicit Matrices

Ryan Adams, Harvard University
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/tba
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0:53:37

Stochastic Gradient MCMC for Independent and Dependent Data Sources

Emily Fox, University of Washington
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/emily-fox-2017-05-01
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1:2:6

On Gradient-Based Optimization: Accelerated, Distributed, Asynchronous and Stochastic

Michael Jordan, UC Berkeley
Computational Challenges in Machine Learninghttps://simons.berkeley.edu/talks/michael-jordan-2017-5-2
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0:48:31

Sampling Polytopes: From Euclid to Riemann

Yin Tat Lee, Microsoft Research and University of Washington
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/yin-tat-lee-2017-5-2
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0:38:54

Understanding Generalization in Adaptive Data Analysis

Vitaly Feldman, IBM Almaden
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/vitaly-feldman-2017-5-2
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0:39:37

Your Neural Network Can't Learn Mine

John Wilmes, Georgia Institute of Technology
Computational Challenges in Machine Learning
https://simons.berkeley.edu/talks/tba-2
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