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1
Introduction
2
Definition
3
Decreasing Marginals
4
Modular Functions
5
Optimization
6
Value Oracle Model
7
Unconstrained vs Unconstrained
8
Submodular functions
9
Directed case
10
History
11
Greedy
12
Algorithm
13
Main Observation
14
Analysis
15
Randomization
16
Relaxations
17
MultiLinear Extension
18
Constraints
19
Continuous Greedy
20
Modular Welfare Problem
21
Continuous Greedy Algorithm
Description:
Explore recent advancements in submodular maximization through this comprehensive lecture, covering both constrained and unconstrained scenarios, as well as monotone and non-monotone submodular functions. Delve into key concepts such as decreasing marginals, modular functions, and the value oracle model. Examine the differences between unconstrained and constrained optimization, and learn about the directed case and its historical context. Gain insights into greedy algorithms, randomization techniques, and relaxations, including the multilinear extension. Investigate constraints and their impact on optimization, and understand the continuous greedy algorithm and its application to the modular welfare problem. This in-depth presentation, part of the Hausdorff Trimester Program on Combinatorial Optimization, offers a thorough exploration of cutting-edge research in submodular function maximization.

Recent Results on Maximizing Submodular Functions

Hausdorff Center for Mathematics
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