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Distributed Submodular Maximization in Massive Datasets
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Classroom Contents
The Power of Randomization - Distributed Submodular Maximization on Massive Datasets
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- 1 Distributed Submodular Maximization in Massive Datasets
- 2 Combinatorial Optimization
- 3 Submodularity
- 4 Example: Multimode Sensor Coverage
- 5 Example: Identifying Representative
- 6 Need for Parallelization
- 7 Problem Definition
- 8 Greedy Algorithm
- 9 Performance of Distributed Greedy
- 10 Revisiting the Analysis
- 11 Power of Randomness
- 12 Intuition
- 13 Analysis (Preliminaries)
- 14 Analysis (Sketch)
- 15 Generality
- 16 Non-monotone Functions
- 17 Future Directions
