Upcoming Events

Machine Learning and Causal Inference for Heterogeneous Treatment Effects

Susan Athey
Machine Learning and Causal Inference for Heterogeneous Treatment Effects
Fri, Feb 22, 2019, 12:00 pm to 1:00 pm
This talk will review recently developed methods to apply machine learning methods to causal inference problems, including the problems of estimating heterogeneous treatment effects, for example, in A/B testing, as well as in estimating optimal treatment assignment policies.
Speaker(s):
Susan Athey
The Economics of Technology Professor, Stanford Graduate School of Business
Tags: Seminars

Binary star science with sparse, noisy, and missing data

Adrian Price-Whelan
Binary star science with sparse, noisy, and missing data
Fri, Feb 22, 2019, 2:00 pm to 3:00 pm
Many open questions in astrophysics hinge on a better understanding of binary star populations (their occurrence rate, orbital parameter distributions, and how these vary with environment).Yet, most of what we know about binary star statistics comes from just a few hundred stars nearest to the sun. Contemporary astronomical surveys have the...
Location: Peyton Auditorium, Room 145
Speaker(s):
Adrian Price-Whelan
Lyman Spitzer, Jr. Postdoctoral Fellow
Tags: Seminars

Fitting Convex Sets to Data

Venkat Chandrasekaran
Fitting Convex Sets to Data
Mon, Mar 11, 2019, 4:30 pm to 5:30 pm
A number of problems in signal processing may be viewed conceptually as fitting a convex set to data.  In vision and learning, the task of identifying a collection of features or atoms that provide a concise description of a dataset has been widely studied under the title of dictionary learning or sparse coding.  In convex-geometric terms, this...
Location: Equad, B205
Speaker(s):
Venkat Chandrasekaran, Professor of Computing and Mathematical Sciences and Electrical Engineering
CalTech
Tags: Seminars

Undergraduate Certificate - Final Independent Work Title and Abstract Due

Undergraduate Certificate
Undergraduate Certificate - Final Independent Work Title and Abstract Due
Mon, Apr 8, 2019, 5:00 pm

Deadline for Final Independent Work Title and Abstract. 

Location: 26 Prospect Ave, Princeton NJ
Tags: Undergrad_Certificate

Undergraduate Certificate - Independent Work Posters Due by Noon

Undergraduate Certificate
Undergraduate Certificate - Independent Work Posters Due by Noon
Mon, May 6, 2019, 12:00 pm

Deadline for Independent Work Posters is at Noon.

Tags: Undergrad_Certificate

Undergraduate Certificate - Independent Work Papers Due

Undergraduate Certificate
Undergraduate Certificate - Independent Work Papers Due
Mon, May 13, 2019, 5:00 pm

Deadline for Independent Work Papers.

Tags: Undergrad_Certificate

CSML 2019 Poster Session

poster session
CSML 2019 Poster Session
Tue, May 14, 2019, 12:00 pm
Location: Carl A. Fields Center, Multipurpose Room 104
Tags: Undergrad_Certificate
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Events Archive

Undergraduate Certificate - Submission of Independent Work Title and Abstract

Undergraduate Certificate
Undergraduate Certificate - Submission of Independent Work Title and Abstract

Deadline for Submission of Independent Work Title and Abstract.

Location: 26 Prospect Ave, Princeton NJ
Tags: Undergrad_Certificate

Decoding the Milky Way Galaxy

Ana Bonaca
Decoding the Milky Way Galaxy
Stars residing in the Milky Way halo hold the key to the origin of our Galaxy. The stellar halo has traditionally been inaccessible as it contains only one percent of stars in the Galaxy. However, novel data sets have enabled us to confidently identify thousands of halo stars in a high-dimensional space of stellar positions, velocities and...
Location: Peyton Hall, Room 145
Speaker(s):
Ana Bonaca
Institute for Theory and Computation, Harvard-Smithsonian Center for Astrophysics
Decoding the Milky Way Galaxy
Tags: Seminars

Sparse matrices in sparse analysis

Anna Gilbert
Sparse matrices in sparse analysis
In this talk, I will give two vignettes on the theme of sparse matrices in sparse analysis. The first vignette covers work from compressive sensing in which we want to design sparse matrices (i.e., matrices with few non-zero entries) that we use to (linearly) sense or measure compressible signals.
Location: B205 Engineering Quadrangle
Speaker(s):
Anna Gilbert
University of Michigan
Sparse matrices in sparse analysis
Tags: Seminars

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