Media Summary: Stefanie Jegelka, MIT Foundations of Machine ... Niv Buchbinder, Tel Aviv University Discrete Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ...

Lecture 8 Submodular Functions Optimization - Detailed Analysis & Overview

Stefanie Jegelka, MIT Foundations of Machine ... Niv Buchbinder, Tel Aviv University Discrete Models, Inference and Algorithms Broad Institute of MIT and Harvard September 26, 2018 MIA Meeting: ... The Image Analysis Class 2013 by Prof. Fred Hamprecht. It took place at the HCI / Heidelberg University during the summer term ... A Google Algorithms TechTalk, 2021/01/14, presented by Mehrdad Ghadiri.

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Lecture 8, Submodular Functions, Optimization, & Applications to Machine Learning
Submodularity - Stefanie Jegelka - MLSS 2017
MIT 6.854 Spring 2016 Lecture 13: Submodular Functions
MIT 6.854 Spring 2016 Lecture 12: From Separation to Optimization and Back; Ellipsoid Method
Submodularity: Theory and Applications I
Submodular Optimization
Lecture 8: Optimization problems with decomposable structure
Optimization in Machine Learning (Lecture 8): Polyhedra, Extensions, and Submodular Minimization
MIA: Yaron Singer, Maximizing submodular functions exponentially faster; Primer: Adam Breuer
8.3 Quadratic PBFs with submodular terms | Image Analysis Class 2013
Beyond Submodular Maximization via One-Sided Smoothness and Meta-Submodularity
ISIT 2018 - Jeffrey Bilmes and Amin Karbasi - Submodularity in Information and Data Science
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Lecture 8, Submodular Functions, Optimization, & Applications to Machine Learning

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

Submodular Functions

Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

Recorded by Andrew Xia 2016.

MIT 6.854 Spring 2016 Lecture 12: From Separation to Optimization and Back; Ellipsoid Method

MIT 6.854 Spring 2016 Lecture 12: From Separation to Optimization and Back; Ellipsoid Method

Recorded by Andrew Xia.

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-09-13-17 Discrete

Lecture 8: Optimization problems with decomposable structure

Lecture 8: Optimization problems with decomposable structure

Course: Advanced

Optimization in Machine Learning (Lecture 8): Polyhedra, Extensions, and Submodular Minimization

Optimization in Machine Learning (Lecture 8): Polyhedra, Extensions, and Submodular Minimization

Lecture 8

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: ...

8.3 Quadratic PBFs with submodular terms | Image Analysis Class 2013

8.3 Quadratic PBFs with submodular terms | Image Analysis Class 2013

The Image Analysis Class 2013 by Prof. Fred Hamprecht. It took place at the HCI / Heidelberg University during the summer term ...

Beyond Submodular Maximization via One-Sided Smoothness and Meta-Submodularity

Beyond Submodular Maximization via One-Sided Smoothness and Meta-Submodularity

A Google Algorithms TechTalk, 2021/01/14, presented by Mehrdad Ghadiri.

ISIT 2018 - Jeffrey Bilmes and Amin Karbasi - Submodularity in Information and Data Science

ISIT 2018 - Jeffrey Bilmes and Amin Karbasi - Submodularity in Information and Data Science

2018 ISIT Tutorial Vail, CO - 6/17/18