Research map / Learning theory and algorithms / Clustering
Gradient Based Clustering
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace the exact K-means center update with a gradient step | K-means clustering · MNIST digits 1 through 7 | clustering accuracy | Helped |
| Replace the exact K-means center update with a gradient step | K-means clustering · MNIST digits 1 through 7 | iteration-wise convergence speed | Hurt |
| Replace the exact K-means center update with a gradient step | K-means clustering · Iris | clustering accuracy | No clear effect |
| Replace the exact K-means center update with a gradient step | K-means clustering · Iris | iteration-wise convergence speed | Hurt |
| Use a gradient update with Huber loss instead of the competing Huber fixed-point update | Huber clustering · MNIST with Gaussian noise, variance 1 | clustering accuracy | No clear effect |
| Use a gradient update with Huber loss instead of the competing Huber fixed-point update | Huber clustering · MNIST with Gaussian noise, variance 2 | clustering accuracy | Helped |
| Use a gradient update with Huber loss instead of the competing Huber fixed-point update | Huber clustering · Iris with Gaussian noise | clustering accuracy | Mixed |
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