Media Summary: The study of combinatorial problems with a A brief introduction to the NIPS 2017 paper "Non-monotone Mahdi Soltanolkotabi, University of Southern California Fast ...

Continuous Methods For Submodular Maximization - Detailed Analysis & Overview

The study of combinatorial problems with a A brief introduction to the NIPS 2017 paper "Non-monotone Mahdi Soltanolkotabi, University of Southern California Fast ... A Google Algorithms TechTalk, 2021/01/14, presented by Mehrdad Ghadiri. In this lecture we consider the problem of Stefanie Jegelka, MIT Foundations of Machine ...

NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach ( Randomization is a fundamental tool used in many theoretical and practical areas of computer science. We study here the role of ... The next two lectures revisit the problem of

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Continuous Methods for Submodular Maximization
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms
Submodularity - Stefanie Jegelka - MLSS 2017
5-2 Submodular Maximization
MIT 6.854 Spring 2016 Lecture 13: Submodular Functions
Nonconvex Optimization for High-dimensional Learning: From ReLUs to Submodular Maximization
Beyond Submodular Maximization via One-Sided Smoothness and Meta-Submodularity
10.3 Submodular Functions, Part III
Submodularity: Theory and Applications I
[2024/25 Winter Lecture] Lecture 10. Discrete and Continuous Submodular Function Maximization
NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach (Submodularity: Discrete to Continuous)
Niv Buchbinder: Deterministic Algorithms for Submodular Maximization Problems
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Continuous Methods for Submodular Maximization

Continuous Methods for Submodular Maximization

The study of combinatorial problems with a

Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms

Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms

A brief introduction to the NIPS 2017 paper "Non-monotone

Submodularity - Stefanie Jegelka - MLSS 2017

Submodularity - Stefanie Jegelka - MLSS 2017

This is Stefanie Jegelka's lecture on

5-2 Submodular Maximization

5-2 Submodular Maximization

Submodular Maximization

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

MIT 6.854 Spring 2016 Lecture 13: Submodular Functions

Recorded by Andrew Xia 2016.

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 ...

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.

10.3 Submodular Functions, Part III

10.3 Submodular Functions, Part III

In this lecture we consider the problem of

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 ...

[2024/25 Winter Lecture] Lecture 10. Discrete and Continuous Submodular Function Maximization

[2024/25 Winter Lecture] Lecture 10. Discrete and Continuous Submodular Function Maximization

Lecture #10: Discrete and

NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach (Submodularity: Discrete to Continuous)

NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach (Submodularity: Discrete to Continuous)

NIPS 2016 Workshop on Nonconvex Optimization: Francis Bach (

Niv Buchbinder: Deterministic Algorithms for Submodular Maximization Problems

Niv Buchbinder: Deterministic Algorithms for Submodular Maximization Problems

Randomization is a fundamental tool used in many theoretical and practical areas of computer science. We study here the role of ...

10.6 Continuous Greedy, Part I

10.6 Continuous Greedy, Part I

The next two lectures revisit the problem of