Regularized Submodular Maximization At Scale Information Guide

  1. About of Regularized Submodular Maximization At Scale
  2. Important Facts
  3. Developments
  4. Detailed Analysis
  5. Conclusion

About of Regularized Submodular Maximization At Scale

Regularized Submodular Maximization at Scale Guide
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Important Facts

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

Full Nonconvex Optimization for High-dimensional Learning: From ReLUs to Submodular Maximization Guide
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Rishabh Iyer: Submodular Optimization and Data Summarization with Applications to Computer Vision
Rishabh Iyer: Submodular Optimization and Data Summarization with Applications to Computer Vision
A2.D – Optimal Streaming Algorithms for Submodular Maximization with Cardinality Constraints
A2.D – Optimal Streaming Algorithms for Submodular Maximization with Cardinality Constraints
10.3 Submodular Functions, Part III
10.3 Submodular Functions, Part III
Structured Regularization Summer School - F. Bach - 19/06/2017
Structured Regularization Summer School - F. Bach - 19/06/2017
IJCAI 2020 Tutorial Part II: Submodular Optimization for Data, Feature, and Topic Summarization.
IJCAI 2020 Tutorial Part II: Submodular Optimization for Data, Feature, and Topic Summarization.
10.2 Submodular Functions, Part II
10.2 Submodular Functions, Part II
Nonconvex Optimization for High Dimensional Learning: From Phase Retrieval to Submodular Maximizatio
Nonconvex Optimization for High Dimensional Learning: From Phase Retrieval to Submodular Maximizatio
Submodularity: Theory and Applications I
Submodularity: Theory and Applications I
Provable Submodular Minimization via Wolfe’s Algorithm
Provable Submodular Minimization via Wolfe’s Algorithm
Lecture 25: Submodular Maximization with Cardinality Constraint: Streaming
Lecture 25: Submodular Maximization with Cardinality Constraint: Streaming
Morteza Zadimoghaddam - Submodular Maximization for Data Summarization
Morteza Zadimoghaddam - Submodular Maximization for Data Summarization

Detailed Analysis

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Last Updated: October 1, 2026

Conclusion

Full Beyond Submodular Maximization via One-Sided Smoothness and Meta-Submodularity Guide
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Summary

Ehsan Kazemi, Shervin Minaee, Moran Feldman, and Amin Karbasi. Yandex School of Data Analysis Conference Machine Learning: Prospects and Applications ... Mahdi Soltanolkotabi, University of Southern California simons.berkeley.edu/talks/mahdi-soltanolkotabi-10-05-17 Fast ... A Google Algorithms TechTalk, 2021/01/14, presented by Mehrdad Ghadiri. ICALP-A 2020 Optimal Streaming Algorithms for In this lecture we consider the problem of IJCAI 2020 Tutorial Presented by Rishabh Iyer and Ganesh Ramakrishnan. Tutorial Website: ... In this lecture we give the basic greedy algorithm, and give the proof by Wolsey, Nemhauser and Fisher stating that if \mathcal{I} is ... Dr. Mahdi Soltanolkotabi University of Southern California *** Abstract: Many problems of contemporary interest in signal ... Stefanie Jegelka, MIT simons.berkeley.edu/talks/andreas-krause-stefanie-jegelka-01-23-2017-1 Foundations of Machine ... Owing to several applications in large So I went in LA we have been talking about somewhat the Dr. Morteza Zadimoghaddam Research Scientist @ Google Scientific Background Research Scientist @ Microsoft ...

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