Tutorial on Deep Learning IV
Ruslan Salakhutdinov, Carnegie Mellon University
https://simons.berkeley.edu/talks/ruslan-salakhutdinov-01-26-2017-4
Foundations of Machine Learning Boot Camp
Other Videos By Simons Institute for the Theory of Computing
| 2017-01-31 | Some of My Favorite Open Problems on Expanders and Extractors |
| 2017-01-30 | Two Existence Proofs of Ramanujan Graphs |
| 2017-01-30 | Ramanujan Covers |
| 2017-01-30 | Extractors for Algebraic Sources |
| 2017-01-30 | An Efficient Reduction from Non-Malleable Extractors to Two-Source Extractors, and... |
| 2017-01-30 | Correlation Breakers, Independence-Preserving Mergers, and their Applications |
| 2017-01-30 | Explicit Constructions of Two-Source Extractors and Ramsey Graphs |
| 2017-01-27 | Natural Language Understanding: Foundations and State-of-the-Art |
| 2017-01-27 | Tensor Decompositions for Learning Latent Variable Models II |
| 2017-01-27 | Tensor Decompositions for Learning Latent Variable Models I |
| 2017-01-26 | Tutorial on Deep Learning IV |
| 2017-01-26 | Tutorial on Deep Learning III |
| 2017-01-26 | Tutorial on Deep Learning II |
| 2017-01-26 | Tutorial on Deep Learning I |
| 2017-01-25 | Nonparametric Bayesian Methods: Models, Algorithms, and Applications IV |
| 2017-01-25 | Nonparametric Bayesian Methods: Models, Algorithms, and Applications II |
| 2017-01-25 | Nonparametric Bayesian Methods: Models, Algorithms, and Applications III |
| 2017-01-25 | Nonparametric Bayesian Methods: Models, Algorithms, and Applications I |
| 2017-01-24 | Deep Robotic Learning |
| 2017-01-24 | Interactive Learning of Classifiers and Other Structures |
| 2017-01-24 | A Tutorial on Reinforcement Learning II |
Tags: Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Foundations of Machine Learning Boot Camp
Ruslan Salakhutdinov
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