Beyond Submodular Maximization Via One

Media Summary: A Google Algorithms TechTalk, 2021/01/14, presented by Mehrdad Ghadiri. Constrained Submodular Maximization Beyond I/e Speaker: Gözde Özcan, Northeastern University Title:

Beyond Submodular Maximization Via One - Detailed Analysis & Overview

A Google Algorithms TechTalk, 2021/01/14, presented by Mehrdad Ghadiri. Constrained Submodular Maximization Beyond I/e Speaker: Gözde Özcan, Northeastern University Title: What is Gradient Descent really doing? Gradient Descent is Presented at the IPCO Conference 2020 held at the London School of Economics and Political Science The study of combinatorial problems with a

Tim Roughgarden and Joshua Wang An Optimal Learning Algorithm for Online Unconstrained Yuval Filmus Member, School of Mathematics October 7, 2014 Monotone In this lecture we consider the problem of Yandex School of Data Analysis Conference Machine Learning: Prospects and Applications ...

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

Constrained Submodular Maximization Beyond I/e

Submodular Maximization via Taylor Series Approximation (SDM21)

Three Perspectives on Gradient Descent (And You Only Know One)

Xueyu Shi - Sequence Independent Lifting for Submodular Maximization

5-2 Submodular Maximization

Beyond Vector Search: Building a “Brain” with Graph RAG | THE INFINITY AI BUILDFEST 2026

Continuous Methods for Submodular Maximization

An Optimal Learning Algorithm for Online Unconstrained Submodular Maximization

Monotone submodular maximization over a matroid - Yuval Filmus

10.3 Submodular Functions, Part III

5B 1 Revisiting Modified Greedy Algorithm for Monotone Submodular Maximization with a Knapsack Cons

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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.

Constrained Submodular Maximization Beyond I/e

Constrained Submodular Maximization Beyond I/e

Constrained Submodular Maximization Beyond I/e

Submodular Maximization via Taylor Series Approximation (SDM21)

Submodular Maximization via Taylor Series Approximation (SDM21)

Speaker: Gözde Özcan, Northeastern University Title:

Three Perspectives on Gradient Descent (And You Only Know One)

Three Perspectives on Gradient Descent (And You Only Know One)

What is Gradient Descent really doing? Gradient Descent is

Xueyu Shi - Sequence Independent Lifting for Submodular Maximization

Xueyu Shi - Sequence Independent Lifting for Submodular Maximization

Presented at the IPCO Conference 2020 held at the London School of Economics and Political Science

5-2 Submodular Maximization

5-2 Submodular Maximization

This is important this linear program is

Beyond Vector Search: Building a “Brain” with Graph RAG | THE INFINITY AI BUILDFEST 2026

Beyond Vector Search: Building a “Brain” with Graph RAG | THE INFINITY AI BUILDFEST 2026

Beyond

Continuous Methods for Submodular Maximization

Continuous Methods for Submodular Maximization

The study of combinatorial problems with a

An Optimal Learning Algorithm for Online Unconstrained Submodular Maximization

An Optimal Learning Algorithm for Online Unconstrained Submodular Maximization

Tim Roughgarden and Joshua Wang An Optimal Learning Algorithm for Online Unconstrained

Monotone submodular maximization over a matroid - Yuval Filmus

Monotone submodular maximization over a matroid - Yuval Filmus

Yuval Filmus Member, School of Mathematics October 7, 2014 Monotone

10.3 Submodular Functions, Part III

10.3 Submodular Functions, Part III

In this lecture we consider the problem of

5B 1 Revisiting Modified Greedy Algorithm for Monotone Submodular Maximization with a Knapsack Cons

5B 1 Revisiting Modified Greedy Algorithm for Monotone Submodular Maximization with a Knapsack Cons

... candidate with a star that

Summarizing Massive Data Sets via Large-Scale Submodular Maximization - Prof. Andreas Krause

Summarizing Massive Data Sets via Large-Scale Submodular Maximization - Prof. Andreas Krause

Yandex School of Data Analysis Conference Machine Learning: Prospects and Applications ...