Submodularity and Optimization -- Jeff Bilmes (Part 1) Published 2014-11-17 Download video MP4 360p Download video MP4 720p Recommendations 1:26:26 Submodularity and Optimization -- Jeff Bilmes (Part 2) 45:02 3. String Manipulation, Guess and Check, Approximations, Bisection 1:30:56 Bayesian Uncertainty Quantification for Differential Equations -- Mark Girolami (Part 1) 17:36 The Discrete Fourier Transform (DFT) 12:10 5-1 Submodularity 1:28:22 Deep Learning -- Yoshua Bengio (Part 1) 12:33 (M6E4) [Microeconomics] Cost Functions 1:33:57 Probabilistic Programming and Bayesian Nonparametrics -- Frank Wood (Part 1) 20:33 Gradient descent, how neural networks learn | Chapter 2, Deep learning 13:51 10.1 Submodular Functions, Part I 26:53 Gauss's Divergence Theorem 15:55 Visualize Spectral Decomposition | SEE Matrix, Chapter 2 43:31 2. Branching and Iteration 18:32 Backpropagation Details Pt. 1: Optimizing 3 parameters simultaneously. 1:04:01 Submodularity: Theory and Applications I 1:18:53 Jan Vondrak - Submodular Functions and Their Applications 1:06:59 MIT 6.854 Spring 2016 Lecture 13: Submodular Functions 16:28 SVD Visualized, Singular Value Decomposition explained | SEE Matrix , Chapter 3 #SoME2 1:44:29 EE596B Lecture 2, Submodular Functions, Optimization, and Applications to Machine Learning 1:23:26 Kernel methods and computational biology -- Jean-Philippe Vert (Part 1) Similar videos 1:27:39 Submodularity and Optimization -- Jeff Bilmes (Part 3) 2:46:49 ISIT 2018 - Jeffrey Bilmes and Amin Karbasi - Submodularity in Information and Data Science 1:49:49 Lecture 15, Submodular Functions, Optimization, & Applications to Machine Learning 1:27:49 Lecture 19, Submodular Functions, Optimization, & Applications to Machine Learning 1:39:30 Lecture 13, Submodular Functions, Optimization, & Applications to Machine Learning 1:37:01 EE596B Lecture 3, Submodular Functions, Optimization, and Applications to Machine Learning 1:39:38 Lecture 10, Submodular Functions, Optimization, & Applications to Machine Learning 1:40:07 Lecture 8, Submodular Functions, Optimization, & Applications to Machine Learning 1:42:10 Lecture 17, Submodular Functions, Optimization, & Applications to Machine Learning 2:00:25 Lecture 18, Submodular Functions, Optimization, & Applications to Machine Learning 1:31:48 Lecture 11, Submodular Functions, Optimization, & Applications to Machine Learning 1:35:36 EE596B Lecture 7, Submodular Functions, Optimization, & Applications to Machine Learning 19:45 Submodularity in Ranking, Summarization, and Self-attention 1:46:26 Lecture 12, Submodular Functions, Optimization, & Applications to Machine Learning 1:10:34 Speech, Language, & Machine Learning – Jeff A. Bilmes (University of Washington) - April 12, 2005 More results