| Week | Topics | Slides | Other material | Reading |
| Week-01 (03 Jan - 07 Jan) |
Introduction: NP-Hardness recap |
Logistics |
Chapter 8 from Kleinberg and Tardos | |
| Week-02 (09 Jan - 13 Jan) |
Introduction: NP-Hardness recap Approximation Algorithms: Introduction |
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| Week-03 (16 Jan - 20 Jan) |
Approximation Algorithms: Greedy approximation (Makespan, Set cover, Vertex Cover, k-center) Approximation Algorithms: FPTAS for 0-1 Knapsack |
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| Week-04 (23 Jan - 27 Jan) |
Getting around NP-hardness: Discusssion Parameterized algorithms: Vertex Cover Hardness of Approximation: Gap introduction reduction |
- Chapter 10 (section 10.1) from Kleinberg and Tardos - Chapter 19 (Hardness of Approximation) from Vijay Vazirani's Approximation algorithms book |
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| Week-05 (30 Jan - 03 Feb) |
Hardness of Approximation: PCP Theorem, Max-3-SAT, Vertex Cover, Quiz-1 Linear Programming: Problem modelling, ILP, Simplex |
Scan |
- Chapter 19 (Hardness of Approximation) from Vijay Vazirani's Approximation algorithms book - Linear Programming chapter from CLRS |
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| Week-06 (13 Feb - 17 Feb) |
Linear Programming: Simplex, Duality, Rounding | - Linear Programming chapter from CLRS | ||
| Week-07 (20 Feb - 24 Feb) |
Linear Programming: Duality, Rounding Dual fitting, Integrality gap |
Scan | Chandra Chekuri's notes Chapters 2 and 13 from Vazirani book |
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| Week-08 (27 Feb - 03 Mar) |
Linear Programming: Primal-dual, max-flow-min-cut Semidefinite Programming: Quadratic Programs, Vector Program, Max-cut |
Scan Scan |
Nice lecture notes from Mikhail Lavrov that I found on the web |
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| Week-09 (13 Mar - 17 Mar) |
Semidefinite Programming: contd. Data Processing: Johnson Lindenstrauss |
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Foundations of Data Science (Section 2.6, 2.7) |
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| Week-10 (20 Mar - 24 Mar) |
Data Processing: SVD, Quiz-2 | |
Foundations of Data Science (Chapter 3) |
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| Week-11 (27 Mar - 31 Mar) |
Data Processing: SVD | Foundations of Data Science (Chapter 3) |
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| Week-12 (03 Apr - 07 Apr) |
Data Processing: Perceptron, Generalization bounds | Foundations of Data Science (Chapter 5) |
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| Week-13 (10 Apr - 14 Apr) |
Data Processing: Generalization bounds, VC dimension | Foundations of Data Science (Chapter 5) |
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| Week-14 (17 Apr - 21 Apr) |
Data Processing: VC dimension, Streaming algorithms | Foundations of Data Science (Chapter 5, 6) |
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| Week-15 (24 Apr - 28 Apr) |
Data Processing: Streaming algorithms (distinct, majority, moments), Quiz-3 |
Foundations of Data Science (Chapter 6) |