Discrete Optimization for Vision and Learning

Who? How? M. Pawan Kumar Associate Professor Ecole Centrale Paris Nikos Komodakis Associate Professor Ecole des Ponts 7 lectures. 1 exam. All in English.

Where? When? Starts on 16 th January, 09h45 – 13h00

Why? How can I change the scenery?

Why? Where is my car? car road grass tree sky

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 – Coursera – 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