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CS8850: Main definitions from lecture 2 (Sergey Plis) View | |
CS8850: Learning via Uniform Convergence (Sergey Plis) View | |
CS8850: Reverse mode AD (Sergey Plis) View | |
CS8850: Dual formulation of Linear SVM (Sergey Plis) View | |
CS8850: A (Sergey Plis) View | |
CS8850: Soft K-means (Sergey Plis) View | |
26-e LFD: The similarity for designing a kernel is task specific: strings, text, graphs, images. (M MI) View | |
Intro to Local (non-parametric) Density Estimation Methods, slecture (Project Rhea) View | |
Non-parametric density estimation - 2: Parzen window (Sarper Alkan) View | |
MLVU 8.4: Expectation-maximization from first principles (MLVU) View |