Introduction of Lecture 2 Approximation Algorithms For Stochastic Combinatorial Optimization Mini Course
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Approximation Algorithms for Stochastic Optimization II
LPs and Convex Programming Relaxations and Rounding for Stochastic Problems
Approximation Algorithms for Stochastic Optimization I
Approximation Algorithms for Stochastic Minimum Norm Combinatorial Optimization
03-712 Lecture 2
Approximation Algorithms for Optimization under Uncertainty
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Last Updated: October 24, 2026
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Kamesh Munagala, Duke University simons.berkeley.edu/talks/kamesh-munagala-08-22-2016- Abstract: In this work, we introduce and study Anupam Gupta, Carnegie Mellon University simons.berkeley.edu/talks/anupam-gupta-09-11-17 Discrete Sharat Ibrahimpur (Waterloo); Chaitanya Swamy (Waterloo) Instructor : Sharat Ibrahimpur Affiliation : ETH Zurich Abstract : Uncertainty is ubiquitous in real-world problems, highlighting a ...
Lecture 2 Approximation Algorithms For Stochastic Combinatorial Optimization Mini Course.pdf
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