M. Pawan Kumar 
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PART I (TAUGHT BY NIKOS KOMODAKIS) SLIDES FOR PART II
Lecture 1: Reparameterization, belief propagation.
Lecture 2, Part 1: Convex relaxations.
Lecture 2, Part 2: Linear programming relaxation.
Lecture 3, Part 1: Treereweighted message passing.
Lecture 3, Part 2: Dual decomposition.
Lecture 4, Part 1: Roundingbased moves.
Lecture 4, Part 2: Sumproduct belief propagation.
Lecture 4, Part 3: Minimizing free energy. REFERENCES
The following paper provides a comparison of different convex relaxations.
The following paper describes the sequential TRW algorithm. It also provides a brief description of belief propagation as reparameterization (subsection 2.2).
The following paper describes the dual decomposition algorithm.
The following paper presents an analysis of roundingbased movemaking algorithms. PROGRAMMING ASSIGNMENT FINAL EXAM FOR PART II Model Exam Paper 1 (Difficult). Model Exam Paper 2 (Easy). 