Tutorial on Deep Learning II
Ruslan Salakhutdinov, Carnegie Mellon University
https://simons.berkeley.edu/talks/ruslan-salakhutdinov-01-26-2017-2
Foundations of Machine Learning Boot Camp
Other Videos By Simons Institute for the Theory of Computing
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 |
2017-01-24 | A Tutorial on Reinforcement Learning I |
2017-01-23 | Submodularity: Theory and Applications 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