Dimensionality Reduction - Spring 2010 - Info

*** THURSDAYS 1:30-3:20PM (719 Broadway Bldg, 12th floor) ***

Course info sheet.

Instructor: Sam Roweis
Course Email List:: g22_3033_012_sp10 at cs dot nyu dot edu

Please do NOT send instructors or tutors email about the class directly to their personal accounts.
They are not able to answer class email except to ??? at cs dot nyu dot edu.

Lecture Times: Thursdays 1:30-3:20pm
Lecture Location: 719 Broadway, Room 1221
First Lecture: January 21
Final lecture: April 22. (No lecture March 18.)

Office hours: Thursdays 3:30-4:30pm or by appointment, Broadway 715, room 1206.

Prerequisite: none for NYU grad students, instructor permission otherwise;
Credits: 3, 13 weeks.

Readings
class notes, original papers (assigned), chapters from course textbook

Marking Scheme
weekly readings worth 13% (honour system), 3 assignments worth 18% each, one project worth 33%

Auditing
If you are not registered in the class, it is possible for you to audit it (sit in on the lectures), but only if you get the instructor's permission and follow some rules. See the audit page for more info.

Course Description

This course will review computational methods for reducing the dimensionality of high dimensional data which lie on or near a manifold of low intrinsic dimensionality. Topics will include: linear methods (such as principal components analysis, factor analysis, singular value decomposition); classic visualizations methods (such as multidimensional scaling and its non-metric variants); and more recent methods based on eigenvectors of Laplacians and convex optimization (such as Kernel PCA, Locally Linear Embedding, Isomap and Maximum Variance Unfolding). Both theoretical and algorithmic properties of the methods will be discussed. Coursework will include small scale computational experiments and readings of primary source research papers.

Some assignments will contain example code implemented in Matlab, but prior knowledge of Matlab is not required and assignments may be completed in the language of the student's choice.

G22-3033 - Dimensionality Reduction || www.cs.nyu.edu/~roweis/dimension_reduction/