Smoothed Analysis of Multiobjective Optimization Heiko R¨oglin∗ Department of Quantitative Economics Maastricht University Maastricht, The Netherlands Email:

Source URL: www.roeglin.org

A Smoothed Analysis of the k-Means Method DAVID ARTHUR, Stanford University, Department of Computer Science BODO MANTHEY, University of Twente, Department of Applied Mathematics ¨ HEIKO ROGLIN

Source URL: wwwhome.math.utwente.nl

Smoothed Analysis of the Condition Numbers and Growth Factors of Matrices Arvind Sankar ∗ Department of Mathematics Massachusetts Institute of Technology

Source URL: www.cs.yale.edu

Smoothed Analysis of the Successive Shortest Path Algorithm∗ Tobias Brunsch † Kamiel Cornelissen

Source URL: www.roeglin.org

Smoothed Analysis of Partitioning Algorithms for Euclidean Functionals∗ Markus Bl¨aser1 Bodo Manthey2

Source URL: www-cc.cs.uni-saarland.de

• Mathematical analysis
• Mathematics
• Analysis
• Generalized functions
• Smooth functions
• Operations research
• Travelling salesman problem
• Distribution
• Limit of a function
• Approximation algorithm
• Convex function
• Euclidean algorithm

CS264: Beyond Worst-Case Analysis Lecture #14: Smoothed Analysis of Pareto Curves∗ Tim Roughgarden† November 5,

Source URL: theory.stanford.edu

• Operations research
• Mathematical optimization
• Mathematics
• Packing problems
• Mathematical analysis
• Academia
• Cryptography
• Knapsack problem
• Multi-objective optimization
• Pareto efficiency
• Probability distribution
• Pareto distribution

Microsoft Word - Alsaleh.doc

Source URL: www.ndia-mich.org

• Numerical analysis
• Computational fluid dynamics
• Computational science
• Mathematical analysis
• Construction equipment
• Engineering vehicles
• Heavy equipment
• Meshfree methods
• Discrete element method
• Smoothed-particle hydrodynamics
• Finite element method
• DEM

CS264: Beyond Worst-Case Analysis The Top 10 List∗ Tim Roughgarden† December 3, 2014 We covered a lot of concepts in this course. To appreciate this, let’s review the overarching narrative of the course via a top 1

Source URL: theory.stanford.edu

• Computational complexity theory
• Theory of computation
• Mathematics
• Analysis of algorithms
• Operations research
• Mathematical optimization
• NP-complete problems
• Smoothed analysis
• Algorithm
• Competitive analysis
• Best
• worst and average case
• Time complexity

CS264: Beyond Worst-Case Analysis Lecture #15: Smoothed Complexity and Pseudopolynomial-Time Algorithms∗ Tim Roughgarden† November 5, 2014

Source URL: theory.stanford.edu

• Computational complexity theory
• Theory of computation
• Operations research
• Complexity classes
• Combinatorial optimization
• Analysis of algorithms
• Knapsack problem
• Simplex algorithm
• Time complexity
• Optimization problem
• NP
• Polynomial-time approximation scheme

CS264: Beyond Worst-Case Analysis Lecture #1: Three Motivating Examples∗ Tim Roughgarden† September 22,

Source URL: theory.stanford.edu

• Computational complexity theory
• Analysis of algorithms
• Operations research
• Linear programming
• Convex optimization
• Algorithm
• Smoothed analysis
• Best
• worst and average case
• Time complexity
• Sorting algorithm
• Merge sort
• Simplex algorithm