Published on: 2022-12-29 05:29:33
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Approximation Algorithms Part I course published by Coursera Online University. How efficiently can you pack the objects in the minimum number of boxes? How can you cluster nodes in a way that cheaply divides the network into pieces around multiple hubs? These are examples of NP-hard combinatorial optimization problems. It is most likely impossible to solve such problems efficiently, so we aim to provide an approximate solution that can be computed in polynomial time while having provable guarantees that its cost is relative to optimality.
This course takes the knowledge of a standard undergraduate algorithm course and places particular emphasis on algorithms that can be designed using linear programming, a popular and surprisingly successful technique in the field. By taking this course, you will be exposed to a wide range of problems in theoretical computer science fundamentals and powerful design and analysis techniques. Upon completion, you will be able to recognize, when faced with a new combinatorial optimization problem, whether it is close to one of the few well-known fundamental problems, and you will be able to find linear programming relaxations. and use random rounding to try to solve your own. The problem of the course content and especially the course assignments is theoretical in nature and without programming assignments.
This is the first of a two-part course on approximate algorithms.
Week 1
Vertex cover and Linear Programming
Week 2
Knapsack and Rounding
Week 3
Bin Packing, Linear Programming and Rounding
Week 4
Set Cover and Randomized Rounding
Week 5
Multiway Cut and Randomized Rounding
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Subtitle: English
Quality: 720p
1.60 GB
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