Media Summary: Stefanie Jegelka, MIT Foundations of Machine ... Niv Buchbinder, Tel Aviv University Discrete Many problems in machine learning that involve discrete structures or subset selection may be phrased in the language of ...

Submodular Optimization - Detailed Analysis & Overview

Stefanie Jegelka, MIT Foundations of Machine ... Niv Buchbinder, Tel Aviv University Discrete Many problems in machine learning that involve discrete structures or subset selection may be phrased in the language of ... The 32nd International Conference on Algorithmic Learning Theory (ALT 2021) Title: Here we have an example of a non-decreasing Machine Learning Work Shop - Session 2 - Jeff Bilmes - 'Why

Zhipeng Liu at the Clean Energy Insitute at University of Washington demonstrates an algorithm using Matlab and Matpower that ... Mahdi Soltanolkotabi, University of Southern California Fast ...

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5-2 Submodular Maximization
Submodularity: Theory and Applications I
Submodular Optimization
Submodular Optimization and Machine Learning - Part 1
Submodularity - Stefanie Jegelka - MLSS 2017
Submodularity and Optimization -- Jeff Bilmes (Part 1)
Submodular Combinatorial Information Measures with Applications in Machine Learning
apricot: Submodular Selection for Data Summarization | SciPy 2019 | Jacob Schreiber
Reflection methods for user-friendly submodular optimization
5-1 Submodularity
Machine Learning Work Shop  - Why Submodularity is Important to Machine Learning
Submodular Optimization for Voltage Control in Power Systems
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5-2 Submodular Maximization

5-2 Submodular Maximization

Submodular Optimization

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

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 ...

Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's lecture on

Submodularity and Optimization -- Jeff Bilmes (Part 1)

Submodularity and Optimization -- Jeff Bilmes (Part 1)

Intro ...

Submodular Combinatorial Information Measures with Applications in Machine Learning

Submodular Combinatorial Information Measures with Applications in Machine Learning

The 32nd International Conference on Algorithmic Learning Theory (ALT 2021) Title:

apricot: Submodular Selection for Data Summarization | SciPy 2019 | Jacob Schreiber

apricot: Submodular Selection for Data Summarization | SciPy 2019 | Jacob Schreiber

Submodular

Reflection methods for user-friendly submodular optimization

Reflection methods for user-friendly submodular optimization

Recently, it has become evident that

5-1 Submodularity

5-1 Submodularity

Here we have an example of a non-decreasing

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

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

Machine Learning Work Shop - Session 2 - Jeff Bilmes - 'Why

Submodular Optimization for Voltage Control in Power Systems

Submodular Optimization for Voltage Control in Power Systems

Zhipeng Liu at the Clean Energy Insitute at University of Washington demonstrates an algorithm using Matlab and Matpower that ...

Nonconvex Optimization for High-dimensional Learning: From ReLUs to Submodular Maximization

Nonconvex Optimization for High-dimensional Learning: From ReLUs to Submodular Maximization

Mahdi Soltanolkotabi, University of Southern California https://simons.berkeley.edu/talks/mahdi-soltanolkotabi-10-05-17 Fast ...