Lecture Topics (tentative)
Video recordings of the lectures up until September 20, 2019, can be found on Mediasite . The video recordings of lectures from CS 6820 in Fall 2018 are also archived.
8/30 — Introduction: course information, start bipartite maximum matching
Reading: Lecture notes on matchings, §1.1-1.2
9/2 — No class due to Labor Day
9/4 — Bipartite maximum matching: Hopcroft-Karp algorithm
Reading: Lecture notes on matchings, §1.3
9/4 — Bipartite maximum matching: Hopcroft-Karp running time analysis
Reading: Lecture notes on matchings, §1.3
9/9 — Minimum-cost bipartite perfect matching: LP relaxation
Reading: Lecture notes on matchings, §3.1
9/11 — Minimum-cost bipartite perfect matching: primal-dual algorithm
Reading: Lecture notes on matchings, §3.2
9/13 — Online matching: greedy algorithm
Reading: Lecture notes on matchings, §4
9/16 — Online matching: RANKING algorithm
Reading: Lecture notes on matchings, §4
9/18 — Network flow: The max-flow min-cut theorem
Reading: Lecture 16 of Dexter Kozen's book "The Design and Analysis of Algorithms"
9/20 — Network flow: a polynomial-time algorithm
Reading: Lecture 17 of Kozen's book
9/23 — Network flow: max-flow min-cut theorem
Reading: Lecture notes on combinatorial consequences of the max-flow min-cut theorem.
9/25 — Network flow: Combinatorial consequences of max-flow min-cut
Reading: Lecture notes on combinatorial consequences of the max-flow min-cut theorem.
9/27 — Network flow: a strongly polynomial algorithm
Reading: Supplementary lecture notes on flows; see also Lecture 18 of Kozen's book
.9/30 — NO CLASS DUE TO ROSH HASHANAH.
10/2 — Linear programming I: Simplex algorithm
Reading: Lecture notes on linear programming, Section 1.
10/4 — Linear programming II: Finishing simplex algorithm
Reading: Lecture notes on linear programming, Section 1.
10/7 — Linear programming III: LP duality
Reading: Lecture notes on linear programming, Section 2.
10/9 — NO CLASS DUE TO YOM KIPPUR.
10/11 — Linear programming IV: Ellipsoid method
Reading: Not yet available.
10/14 — NO CLASS DUE TO FALL BREAK.
10/16 — NP-Completeness I: Introducing NP-completeness reductions
Reading: Kozen's lecture notes on NP-completeness, Lectures 21-22
10/18 — NP-Completeness II: Independent Set
Reading: Kozen's lecture notes on NP-completeness, Lecture 23
10/21 — NP-Completeness III: Max Cut
Reading: Kozen's lecture notes on NP-completeness, Lecture 24
10/23 — Convex Optimization I: Unconstrained convex minimization
Reading: Lecture notes on convex optimization, sections 1-3
10/25 — Convex Optimization II: Constrained convex minimization
Reading: Lecture notes on convex optimization, section 4
10/28 — Submodularity I: Definitions and Lovász extension
Reading: Lecture notes on submodular functions, sections 1-2
10/30 — Submodularity II: Constrained monotone submodular maximization
Reading: Lecture notes on submodular functions, section 4
11/1 — Submodularity III: Packing spanning arborescences
Reading: Lecture notes on submodular functions, section 3
11/4 — Approximation Algorithms I: Set cover
Reading: Lecture notes on approximation algorithms, sections 1 and 2.3
11/6 — Approximation Algorithms II: Vertex cover
Reading: Lecture notes on approximation algorithms, sections 2.1,2.2
11/8 — Approximation Algorithms III: Finish vertex cover, start max cut
Reading: Lecture notes on approximation algorithms, section 3
11/11 — Approximation Algorithms IV: Max cut via semidefinite programming
Reading: Lecture notes on approximation algorithms, section 3
11/13 — The Chernoff bound
Reading: Lecture notes on approximation algorithms, section 4.1
11/15 — Approximation Algorithms V: Randomized routing and sparsest cut
Reading: Lecture notes on approximation algorithms, section 4.2
and notes on sparsest cut in Section 4 of the lecture notes on the multiplicative weights method (from CS 6820, Fall 2016).11/18 — Spectral methods I: Courant-Fischer and the graph Laplacian
Reading: Lecture notes on spectral methods, sections 1-2
11/20 — Spectral methods II: Cheeger's Inequality
Reading: Lecture notes on spectral methods, sections 3-5
11/25 — Spectral methods III: Spectral graph sparsification
Reading: Lecture notes on spectral methods, section 7