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Events Archive

Cosmology with galaxy surveys: from precision to accuracy with data-driven models

Cosmology with galaxy surveys: from precision to accuracy with data-driven models
Immense surveys of the night sky are being conducted to test the origins and evolutions of the Universe as a whole, using distant galaxies and quasars (bright galaxies with active supermassive black holes at their center). This requires modeling the spatial and spectral statistics of those sources in detail using millions of noisy observations,...
Location: PCTS, 407 Jadwin
Speaker(s):
Boris Leistedt
Center of Cosmology and Particle Physics at New York University
Tags: Seminars

Fitting Convex Sets to Data

Fitting Convex Sets to Data
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

The Complexities of Astronomical Data

The Complexities of Astronomical Data
The analysis of astronomical data set reveals an astonishing diversity of astrophysical processes but also a dizzying array of observational complications. I will introduce several approaches to deal with complications like missing data, non-linear error propagation, and overlapping objects. I will concentrate on proximal optimization algorithms...
Location: Peyton Hall Auditorium, Room 145
Speaker(s):
Peter Melchior
Department of Astrophysical Sciences
Tags: Seminars

Astrophysical Inference with Complex, Stochastic Time Series

Astrophysical Inference with Complex, Stochastic Time Series
Astronomical time series—measurements of a celestial source’s brightness as a function of time—are key to probing the physical processes governing the behaviour of these sources on a large range of scales, from small asteroids in our solar system, to supermassive black holes at the centres of galaxies. Modern time domain surveys like the Zwicky...
Location: PCTS, Jadwin Hall Room 407
Speaker(s):
Daniela Huppenkothen
DIRAC Institute and eScience Institute, University of Washington
Tags: Seminars

Binary star science with sparse, noisy, and missing data

Binary star science with sparse, noisy, and missing data
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

Machine Learning and Causal Inference for Heterogeneous Treatment Effects

Machine Learning and Causal Inference for Heterogeneous Treatment Effects
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

Undergraduate Certificate - Submission of Independent Work Title and Abstract

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

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):
Tags: Seminars

Sparse matrices in sparse analysis

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

Rethinking the Role of Optimization in Learning

Rethinking the Role of Optimization in Learning
In this talk, I will overview our recent progress towards understanding how we learn large capacity machine learning models, especially deep neural networks. In the modern practice of deep learning, many successful models have far more trainable parameters compared to the number of training examples.
Location: B205 Engineering Quadrangle
Speaker(s):
Suriya Gunasekar
Toyota Technical Institute
Tags: Seminars

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