'High dimensions' diaporamas de présentation

k-Nearest Neighbors Search in High Dimensions

k-Nearest Neighbors Search in High Dimensions . Tomer Peled Dan Kushnir. Tell me who your neighbors are, and I'll know who you are. Outline. Problem definition and flavors Algorithms overview - low dimensions Curse of dimensionality (d>10..20)

1.53k views • 111 slides

Recent advances in Global Sensitivity Analysis techniques

Recent advances in Global Sensitivity Analysis techniques. S. Kucherenko Imperial College London, UK s.kucherenko@imperial.ac.uk.

906 views • 59 slides

453 views • 34 slides

A decision-theoretic view of image retrieval

A decision-theoretic view of image retrieval. Nuno Vasconcelos Compaq Computer Corporation Cambridge Research Lab http://www.media.mit.edu/~nuno. horses. Texture similarity. Color similarity. Shape similarity. Content-based retrieval.

421 views • 28 slides

Dimensionality Reduction

349 views • 22 slides

Dimensionality Reduction

295 views • 21 slides

Graph Drawing Using Sampled Spectral Distance Embedding (SSDE)

337 views • 19 slides

Nonparametric Methods: Nearest Neighbors

Nonparametric Methods: Nearest Neighbors. Oliver Schulte Machine Learning 726. Instance-based Methods. Model-based methods: estimate a fixed set of model parameters from data. compute prediction in closed form using parameters. Instance-based methods:

465 views • 17 slides

CS5540: Computational Techniques for Analyzing Clinical Data

173 views • 11 slides

Characterization of rotation equivariant additive mappings

Characterization of rotation equivariant additive mappings. Franz Schuster Technical University Vienna.

164 views • 10 slides

A fast and simple neural probabilistic language model for natural language processing

A fast and simple neural probabilistic language model for natural language processing. Presenter: Yifei Guo Supervisor: David Barber. Statistical language model. Goal: model the joint distribution of words in a sentence

376 views • 9 slides