Lectures

LectDateTopicReference
1 01/09 Introduction [MG 4, Go 9]
Hashing
2 01/14 Universal Hashing [Er 5, MU 5.5]
3 01/16 Consistent Hashing [Va 1]
4 01/21 Bloom Filter [MU 5.5]
5 01/23 Sketches, Security Hash Functions [CY 3.4, Ph 11.2, KL 5,6]
Data Compression
6 01/28 Huffman Coding, Entropy [Bl]
7 01/30 Move-to-Front, Sliding Window Methods [Bl]
Similarity Analysis
8 02/04 Distance Measures [Ph 4]
9 02/06 Clustering: k-center, k-means [PH 8, BHK 7]
10 02/11 Clustering: k-means++, hierarchical [Ph 8, BHK 7]
11 02/13 NN Searching: Low Dimensions [HP 2, 17]
12 02/18 NN Searching: LSH [Ph 4.6, HP 18]
13 02/20 NN Searching: Graph Based [IX]
14 02/25 Dimension Reduction [BHK 2, Ma 15]
Linear Algebraic Methods
15 02/27 Principal Component Analysis (PCA) [Ph 7, Va]
Exam 03/04 Midterm 1 (Lectures 1-13)
16 03/06 PCA Applications [Ph 7, Va]
17 03/18 Singular Value Decomposition [Ph 7, BHK 3, Va]
18 03/20/04 Tensor Methods [Va, Mo 3]
19 03/25 Spectral Clustering [Ph 10]
Sampling and Estimation
20 03/27 VC-dimension, eps-net, eps-approx [HP 5, BHK 5]
21 04/01 Reservoir and Importance Sampling [Ph 2, 11.1; Va]
22 04/03 Coresets [HP 23]
23 04/08 Random Walk on Graphs [Ph 10, BHK 4]
24 04/10 MCMC Methods [Ph 10, BHK 4]
Privacy and Fairness
25 04/15 Differential Privacy [DR]
26 04/17 Algorithnic Fairness TBA
Exam 04/22 Midterm 2 (Lectures 14-26)

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