'Jaccard distance' presentation slideshows

Clustering: Partition Clustering

Clustering: Partition Clustering. Lecture outline. Distance/Similarity between data objects Data objects as geometric data points Clustering problems and algorithms K-means K-median K-center. Inter-cluster distances are maximized. Intra-cluster distances are minimized.

563 views • 34 slides

Clustering: Partition Clustering

Clustering: Partition Clustering. Lecture outline. Distance/Similarity between data objects Data objects as geometric data points Clustering problems and algorithms K-means K-median K-center. Inter-cluster distances are maximized. Intra-cluster distances are minimized.

543 views • 34 slides

Mining social networks and their visual semantics from social photos

378 views • 23 slides

Sketching, Sampling and other Sublinear Algorithms: Nearest Neighbor Search

Sketching, Sampling and other Sublinear Algorithms: Nearest Neighbor Search. Alex Andoni (MSR SVC). Nearest Neighbor Search (NNS). Preprocess: a set of points Query: given a query point , report a point with the smallest distance to . Motivation. Generic setup:

310 views • 17 slides

Sketching, Sampling and other Sublinear Algorithms: Nearest Neighbor Search

Sketching, Sampling and other Sublinear Algorithms: Nearest Neighbor Search. Alex Andoni (MSR SVC). Nearest Neighbor Search (NNS). Preprocess: a set of points Query: given a query point , report a point with the smallest distance to . Motivation. Generic setup:

282 views • 17 slides