Revisiting Nearest Neighbors from a Sparse Signal Approximation View
Offered By: Google TechTalks via YouTube
Course Description
Overview
Syllabus
Intro
Revisiting Nearest Neighbors from a Sparse Signal approximation view
What is a neighborhood?
Neighborhood definitions: Kernels (Similarity)
Neighborhood definitions: Local linearity
Interlude: Sparse Signal Approximation
Neighborhood = Sparse signal approximation
Alternative: Basis pursuit
Neighborhoods: Non-negative basis pursuit
Non-Negative Kernel regression (NNK)
Geometry: Kernel Ratio Interval (KRI)
Example
Label propagation using graphs
Experiments: Label propagation
Experiments: Classification
Neighborhoods Summary
Conventional Approach
Solution: NNK-Means
kMeans vs Dictionary learning
Case study: Detecting unseen data using NNK-Means (representational outliers)
NNK-Means atom use in each scenario
NNK-Means for Outlier Detection
NNK-Means Summary
What is deep learning?
Graph based view of deep learning
NNK interpolation at penultimate layer
Taught by
Google TechTalks
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