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Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's lecture on

Submodular Optimization and Machine Learning - Part 1

Submodular Optimization and Machine Learning - Part 1

Many problems in

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

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

IJCAI 2020 Tutorial Part I: Submodular Optimization for Data, Feature, and Topic Summarization.

IJCAI 2020 Tutorial Part I: Submodular Optimization for Data, Feature, and Topic Summarization.

IJCAI 2020 Tutorial Presented by Rishabh Iyer and Ganesh Ramakrishnan. Tutorial Website: ...

EE596B Lecture 3, Submodular Functions, Optimization, and Applications to Machine Learning

EE596B Lecture 3, Submodular Functions, Optimization, and Applications to Machine Learning

Submodular

Optimization in Machine Learning: Lec 7 (Submodular Functions: Definitions, Examples, Properties)

Optimization in Machine Learning: Lec 7 (Submodular Functions: Definitions, Examples, Properties)

Submodular

Submodular Optimization and Machine Learning - Part 2

Submodular Optimization and Machine Learning - Part 2

Many problems in

Lecture 9, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 9, Submodular Functions, Optimization, & Applications to Machine Learning

Lecture 9,

Machine Learning Work Shop  - Why Submodularity is Important to Machine Learning

Machine Learning Work Shop - Why Submodularity is Important to Machine Learning

Machine Learning

Submodular Optimization

Submodular Optimization

Niv Buchbinder, Tel Aviv University https://simons.berkeley.edu/talks/niv-buchbinder-09-13-17 Discrete

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

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

Lecture 8: