Media Summary: Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ... Stefanie Jegelka, MIT Foundations of Machine ... Many problems in machine learning that involve discrete structures or subset selection may be phrased in the language of ...

Lecture 17 Submodular Functions Optimization - Detailed Analysis & Overview

Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ... Stefanie Jegelka, MIT Foundations of Machine ... Many problems in machine learning that involve discrete structures or subset selection may be phrased in the language of ...

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Lecture 17, Submodular Functions, Optimization, & Applications to Machine Learning
Submodularity - Stefanie Jegelka - MLSS 2017
Submodular Optimization
MIA: Yaron Singer, Maximizing submodular functions exponentially faster; Primer: Adam Breuer
Submodularity: Theory and Applications I
Submodular Optimization and Machine Learning - Part 1
MIT 6.854 Spring 2016 Lecture 13: Submodular Functions
Submodularity and Optimization -- Jeff Bilmes (Part 1)
Lecture 19, Submodular Functions, Optimization, & Applications to Machine Learning
Interactive Learning of Mixtures of Submodular Functions
Sketching and Randomization for Distributed Submodular and Coverage Optimization
EE596B Lecture 7, Submodular Functions, Optimization, & Applications to Machine Learning
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Lecture 17, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 17, Submodular Functions, Optimization, & Applications to Machine Learning

Submodular Functions

Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's

Submodular Optimization

Submodular Optimization

Niv Buchbinder, Tel Aviv University https://simons.berkeley.edu/talks/niv-buchbinder-09-13-

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: ...

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 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 ...

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

Recorded by Andrew Xia 2016.

Submodularity and Optimization -- Jeff Bilmes (Part 1)

Submodularity and Optimization -- Jeff Bilmes (Part 1)

Intro ...

Lecture 19, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 19, Submodular Functions, Optimization, & Applications to Machine Learning

Submodular Functions

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-

Sketching and Randomization for Distributed Submodular and Coverage Optimization

Sketching and Randomization for Distributed Submodular and Coverage Optimization

Vahab Mirrokni, Google https://simons.berkeley.edu/talks/vahab-mirrokni-2016-11-

EE596B Lecture 7, Submodular Functions, Optimization, & Applications to Machine Learning

EE596B Lecture 7, Submodular Functions, Optimization, & Applications to Machine Learning

Submodular Functions

Lecture 8, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 8, Submodular Functions, Optimization, & Applications to Machine Learning

Submodular Functions