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Part of Computer Vision Lecture series taught at University of Washington, Seattle in Autumn 2022
0:00 - Introduction to Computational Complexity
2:59 - Example 1
6:17 - Example 2
8:15 - Example 3 (Cosine Similarity)
25:05 - In-class Exercise (Matrix Multiplication)
27:10 - ICE2 (Convolution)
27:30 - kMeans Computational Complexity
34:25 - Image Visualization (tSNE)
41:37 - Total Variation for Image Denoising
45:45 - Norms and Regularizers
51:48 - ICE3 (l1 and l2 norm)
52:31 - Norm and Norm Balls
59:40 - Sparsity for Image Denoising
1:02:40 - Total Variation (TV) Definition
