[Sds-seminars] Fwd: [Teaching-cs] [Department-cs] CS Talk/Manolis Zampetakis, MIT/Nov. 7, 4pm, AKW 200

[Dan Spielman]

---------- Forwarded message ---------
From: Pellegrino, Nancy <nancy.pellegrino at yale.edu>
Date: Thu, Oct 24, 2019 at 11:31 AM
Subject: [Teaching-cs] [Department-cs] CS Talk/Manolis Zampetakis, MIT/Nov.
7, 4pm, AKW 200
To: department-cs at cs.yale.edu <department-cs at cs.yale.edu>


CS Talk - Manolis Zampetakis, MIT

November 7, 2019
AKW 200, 4:00 p.m.

Host: Yang Cai

Title: Computationally and Statistically Efficient Truncated Statistics

Abstract:

Censoring and truncation occur when data falling outside of a subset of the
population are not observable. In practice, it often arises as a result of
saturation of measurement devices, experimental design, and legal or
privacy constraints preventing the use of some of the data. Such phenomena
have been known to affect experimental results in a counterintuitive way,
as per Berkson’s paradox.

In our recent work, we provide the first provably computationally and
statistically efficient methods accomplishing the fundamental task of
statistical estimation for the entire population out of exclusively
censored data. Our first result [w/ Daskalakis, Gouleakis, Tzamos FOCS’18]
assumes that the population follows a multi-dimensional normal distribution
and the survival set is known. In follow-up works, we have extended our
result to the case of censored linear [w/ Daskalakis, Gouleakis, Tzamos
COLT’19], logistic and probit regression [w/ Daskalakis, Ilyas, Rao ‘19]
and we have also explored the case of unknown survival set [w/ Kontonis,
Tzamos FOCS’19].

Bio:

Manolis is a Ph.D. Student in the Theory of Computation Group at MIT
working on theoretical problems in: machine learning and learning theory,
complexity theory, and algorithmic game theory. Before MIT, Manolis was an
undergraduate student at National Technical University of Athens. He has
been an intern at Google Research NYC, Yahoo! Research NYC and Microsoft
Research New England. His graduate studies have been supported by a Google
Ph.D. Fellowship.











_______________________
Nancy Pellegrino
Administrative Assistant

Yale University
Dept. of Computer Science
P.O. Box 208285
New Haven, CT 06520-8285
cpsc.yale.edu

203.432.8023 Phone
203.432.0593 Fax


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