Media Summary: Haotian Jiang (Microsoft Research, Redmond) ... Stefanie Jegelka, MIT Foundations of Machine ... In the past several years, there has been a lot of

Recent Progress On Submodular Function - Detailed Analysis & Overview

Haotian Jiang (Microsoft Research, Redmond) ... Stefanie Jegelka, MIT Foundations of Machine ... In the past several years, there has been a lot of 02 - Bommireddi - Testing submodularity and other properties of valuation functions The Fujishige-Wolfe heuristic is empirically one of the fastest algorithms for Machine Learning Work Shop - Session 2 - Jeff Bilmes - 'Why

Kent Quanrud (Purdue University) Optimization and ... Jeff Bilmes, University of Washington Interactive Learning.

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Recent Progress on Submodular Function Minimization
Submodularity - Stefanie Jegelka - MLSS 2017
Seffi Naor: Recent Results on Maximizing Submodular Functions
Stefanie Jegelka: An introduction to Submodularity, Part 1
Stefanie Jegelka: An introduction to submodularity, Part 2
Submodularity: Theory and Applications I
Recent Developments in Combinatorial Optimization
02 - Bommireddi - Testing submodularity and other properties of valuation functions
Reflection methods for user-friendly submodular optimization
Deeparnab Chakrabarty: Provable Submodular Function Minimization via Fujishige Wolfe Algorithm
Machine Learning Work Shop  - Why Submodularity is Important to Machine Learning
Quotient Sparsification for Submodular Functions
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Recent Progress on Submodular Function Minimization

Recent Progress on Submodular Function Minimization

Haotian Jiang (Microsoft Research, Redmond) ...

Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's lecture on

Seffi Naor: Recent Results on Maximizing Submodular Functions

Seffi Naor: Recent Results on Maximizing Submodular Functions

I will survey

Stefanie Jegelka: An introduction to Submodularity, Part 1

Stefanie Jegelka: An introduction to Submodularity, Part 1

Abstract:

Stefanie Jegelka: An introduction to submodularity, Part 2

Stefanie Jegelka: An introduction to submodularity, Part 2

Abstract:

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 ...

Recent Developments in Combinatorial Optimization

Recent Developments in Combinatorial Optimization

In the past several years, there has been a lot of

02 - Bommireddi - Testing submodularity and other properties of valuation functions

02 - Bommireddi - Testing submodularity and other properties of valuation functions

02 - Bommireddi - Testing submodularity and other properties of valuation functions

Reflection methods for user-friendly submodular optimization

Reflection methods for user-friendly submodular optimization

Recently

Deeparnab Chakrabarty: Provable Submodular Function Minimization via Fujishige Wolfe Algorithm

Deeparnab Chakrabarty: Provable Submodular Function Minimization via Fujishige Wolfe Algorithm

The Fujishige-Wolfe heuristic is empirically one of the fastest algorithms for

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

Quotient Sparsification for Submodular Functions

Quotient Sparsification for Submodular Functions

Kent Quanrud (Purdue University) https://simons.berkeley.edu/talks/kent-quanrud-purdue-university-2023-11-30 Optimization and ...

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.