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Discrete Optimization for Vision and Learning
Who? How?
M. Pawan KumarAssociate ProfessorEcole Centrale Paris
Nikos KomodakisAssociate Professor
Ecole des Ponts
7 lectures. 1 exam. All in English.
Where? When?
Starts on 16th January, 09h45 – 13h00
Why?
How can I change the scenery?
Why?
Where is my car?
car
roadgrass
treeskysky
Why?
Where are my arms? My legs?
What?
Input x
Output y
Energy of y
What?
Energy Minimization
Obtain output y with minimum energy
Learning
Obtain energy using training samples
Energy of y
Syllabus
• Dynamic Programming– e.g. Shortest paths, Belief propagation
• Submodularity– e.g. Max flow, Min cut
• Convex Relaxations– e.g. Linear and semidefinite programming
• Parameter Estimation– e.g. SVM, Maximum likelihood
Two equations (reparameterization) !!
Analysis
• Which algorithm is most efficient?
• Which algorithm is most accurate?
• What algorithm should I use?
• Offered in 2014 as an MVA course
• University of Crete, Greece
• Ecole Centrale Paris– http://cvn.ecp.fr/personnel/pawan
• Coursera– http://www.coursera.org/ecp
Previous Courses
Evaluation
• Programming assignments– Graph Cuts– LP Relaxation
• One written exam– Half “easy” questions– Half “difficult” theoretical questions– “Missing information in publications”
Questions?
• Look at our research and previous courses– Search ‘Nikos Komodakis’– Search ‘M. Pawan Kumar’
• Send us an email– [email protected]– [email protected]
