Week 1: Network Flows, Ford-Fulkerson Algorithm, Edmond-Karp Algorithm
Week 2: Max-Flow Min-Cut Theorem, Application of Network Flows, Edmond’s Matching Algorithm
Week 3: Randomization as Algorithm Design Technique, Karger’s Min Cut Algorithm, Randomized Algorithm for 2-SAT
Week 4: Polynomial Identity Testing, Schwartz-Zippel Lemma Application of PIT: Perfect Bipartite Matching
Week 5: Elementary Concentration Inequalities: Markov, Chebyshev, Chernoff-Hoeffding
Week 6: Markov Chain, Random Walks, Monte Carlo Method, DNF Counting
Week 7: NP-Completeness
Week 8: Approximation Algorithm: Vertex Cover, Set Cover, Travelling Salesman Problem APTAS for Bin Packing
Week 9: FPTAS for Knapsack, Linear Programming Basics
Week 10: Designing Approximation Algorithms using Linear Programs: Rounding, Primal-Dual Schema
Week 11: Parameterized Algorithms: Fixed Parameter Tractable Algorithms, Kernelization, Bounded Search
Week 12: Iterative Compression, Color Coding
DOWNLOAD APP
FOLLOW US