Media Summary: Stefanie Jegelka, MIT Foundations of Machine ... Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ... Jeff Bilmes, University of Washington Interactive Learning.

Lecture 13 Submodular Functions Optimization - Detailed Analysis & Overview

Stefanie Jegelka, MIT Foundations of Machine ... Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ... Jeff Bilmes, University of Washington Interactive Learning. Many problems in machine learning that involve discrete structures or subset selection may be phrased in the language of ... Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his

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Lecture 13, Submodular Functions, Optimization, & Applications to Machine Learning
MIT 6.854 Spring 2016 Lecture 13: Submodular Functions
Submodularity: Theory and Applications I
Submodular Optimization
Submodularity - Stefanie Jegelka - MLSS 2017
MIA: Yaron Singer, Maximizing submodular functions exponentially faster; Primer: Adam Breuer
Interactive Learning of Mixtures of Submodular Functions
5-1 Submodularity
Submodular Optimization and Machine Learning - Part 1
Lecture 13 | Convex Optimization I (Stanford)
Submodular Unsplittable Flow on Trees
Lecture 15, Submodular Functions, Optimization, & Applications to Machine Learning
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Lecture 13, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 13, Submodular Functions, Optimization, & Applications to Machine Learning

Submodular Functions

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

Recorded by Andrew Xia 2016.

Submodularity: Theory and Applications I

Submodularity: Theory and Applications I

Stefanie Jegelka, MIT https://simons.berkeley.edu/talks/andreas-krause-stefanie-jegelka-01-23-2017-1 Foundations of Machine ...

Submodular Optimization

Submodular Optimization

Niv Buchbinder, Tel Aviv University https://simons.berkeley.edu/talks/niv-buchbinder-09-

Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's

MIA: Yaron Singer, Maximizing submodular functions exponentially faster; Primer: Adam Breuer

MIA: Yaron Singer, Maximizing submodular functions exponentially faster; Primer: Adam Breuer

Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ...

Interactive Learning of Mixtures of Submodular Functions

Interactive Learning of Mixtures of Submodular Functions

Jeff Bilmes, University of Washington https://simons.berkeley.edu/talks/jeff-bilmes-02-17-2017 Interactive Learning.

5-1 Submodularity

5-1 Submodularity

Submodular functions

Submodular Optimization and Machine Learning - Part 1

Submodular Optimization and Machine Learning - Part 1

Many problems in machine learning that involve discrete structures or subset selection may be phrased in the language of ...

Lecture 13 | Convex Optimization I (Stanford)

Lecture 13 | Convex Optimization I (Stanford)

Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his

Submodular Unsplittable Flow on Trees

Submodular Unsplittable Flow on Trees

Anna Adamaszek, University of Copenhagen https://simons.berkeley.edu/talks/anna-adamaszek-09-

Lecture 15, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 15, Submodular Functions, Optimization, & Applications to Machine Learning

Submodular Functions

Submodularity and Optimization -- Jeff Bilmes (Part 1)

Submodularity and Optimization -- Jeff Bilmes (Part 1)

Intro ...