<--- Back to Details
First PageDocument Content
Machine learning / Random projection / MinHash / Nearest neighbor search / K-nearest neighbors algorithm / Dimensionality reduction / Normal distribution / Jaccard index / Curse of dimensionality / Standard deviation / Nonlinear dimensionality reduction
Date: 2016-06-04 09:49:43
Machine learning
Random projection
MinHash
Nearest neighbor search
K-nearest neighbors algorithm
Dimensionality reduction
Normal distribution
Jaccard index
Curse of dimensionality
Standard deviation
Nonlinear dimensionality reduction

CS168: The Modern Algorithmic Toolbox Lecture #4: Dimensionality Reduction Tim Roughgarden & Gregory Valiant April 8,

Add to Reading List

Source URL: theory.stanford.edu

Download Document from Source Website

File Size: 190,72 KB

Share Document on Facebook

Similar Documents

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods  Lecture: 2 The SVD and applications Instructor: Sham Kakade

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 2 The SVD and applications Instructor: Sham Kakade

DocID: 1veCZ - View Document

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods  Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 1 The Singular Value Decomposition Instructor: Sham Kakade

DocID: 1vbS6 - View Document

High Precision Screening for Android Malware with Dimensionality Reduction Britton Wolfe Information Analytics and Visualization Center, Indiana Univ.-Purdue Univ. Fort Wayne (IPFW), 2101 E. Coliseum Blvd., Fort Wayne, I

High Precision Screening for Android Malware with Dimensionality Reduction Britton Wolfe Information Analytics and Visualization Center, Indiana Univ.-Purdue Univ. Fort Wayne (IPFW), 2101 E. Coliseum Blvd., Fort Wayne, I

DocID: 1uRCG - View Document

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods  Lecture: 19 Spectral Methods for Learning Vector State-Space Models Instructor: Sham Kakade

Stat 991: Multivariate Analysis, Dimensionality Reduction, and Spectral Methods Lecture: 19 Spectral Methods for Learning Vector State-Space Models Instructor: Sham Kakade

DocID: 1uQvX - View Document

CMSCSpringLarge Scale Learning  Lecture: 4 Dimensionality Reduction and Learning, continued Instructors: Sham Kakade and Greg Shakhnarovich

CMSCSpringLarge Scale Learning Lecture: 4 Dimensionality Reduction and Learning, continued Instructors: Sham Kakade and Greg Shakhnarovich

DocID: 1uCVg - View Document