Tag Archives: x57l

YINS 4/10: John Tsitsiklis, “Safeguarding Privacy in Sequential Decision-Making Problems”

YINS Distinguished Lecturer Series

“Safeguarding Privacy in Sequential Decision-Making Problems”

Speaker: John Tsitsiklis

Clarence J. Lebel Professor of Electrical Engineering and Computer Science at MIT

Wednesday, April 10, 2019 – 12:00pm

Yale Institute for Network Science | 17 Hillhouse Avenue, 3rd floor | New Haven, CT 06511

Abstract: With the increasing ubiquity of large-scale surveillance and data analysis infrastructures, privacy has become a pressing concern in many domains. We propose a framework for studying a fundamental cost vs. privacy tradeoff in dynamic decision-making problems. More concretely, we are interested in ways that an agent can take actions that make progress towards a certain goal, while minimizing the information revealed to a powerful adversary who monitors these actions. We will examine two well-known decision problems (path planning and active learning), and in both cases establish sharp tradeoffs between obfuscation effort and level of privacy. As a byproduct, our analysis also leads to simple yet provably optimal obfuscation strategies. Based on joint work with Kuang Xu (Stanford) and Zhi Xu (MIT).

Speaker bio: John Tsitsiklis is the Clarence J. Lebel Professor of Electrical Engineering and Computer Science at MIT, and a member of the National Academy of Engineering. He obtained his PhD from MIT and joined the faculty in 1984. His research focuses on the analysis and control of stochastic systems, including applications in various domains, from computer networks to finance. He has been teaching probability for over 15 years.

My Notes Related to the NHGRI strategic planning meeting

MAIN event page


TWEETS related to the event


Archived copy of the above in the labdropbox

Liked-Tweets-Related-NHGRI-strategic-planning-meeting–i0g2p18-genome2020-conf0mg in labdropbox


TAGGED links


Message to Yale Community about 2018 Day of Data – small correction

You are invited to attend the 6th annual Yale Day of Data on November 30 in Sterling Memorial Library.

The Yale Day of Data brings together researchers and data experts from across the disciplines to share experiences, challenges, and best practices related to data-intensive research. If you collect, manage, analyze, interpret, or otherwise work with data, this event is for you.

This year’s theme, “Data on Earth,” is intentionally broad, to encompass data about the Earth and the environment, data that help us understand the health and lives of Earth’s inhabitants, and data with global impact.

Keynote: William Michener (Principal Investigator of DataONE, Professor and Director of e-Science Initiatives, University Libraries, University of New Mexico), “Managing Data Throughout the Research Life Cycle to Enable New Science and Support Decision Making”

Talks by Yale faculty and researchers: Tracey Meares, Dena
Schulman-Green, Karen Seto, Alan Gerber, Jessi Cisewski, Casey King, Martin Wainstein & Sophie Janaskie

Registration is now open for the 2018 Yale Day of

New algorithm can create movies from just a few snippets of text | Science | AAAS

Interesting paper by alumnus Renqiang Min on “Video Generation from Text,” using a generative #MachineLearning model.
http://www.AAAI.org/GuideBook2018/16152-72279-GB.pdf (Press report by @SilverJacket: New algorithm can create movies from just a few snippets of text
http://www.ScienceMag.org/news/2018/02/new-algorithm-can-create-movies-just-few-snippets-text )

Video Generation from Text Yitong Li†∗, Martin Renqiang Min‡ , Dinghan Shen† , David Carlson† , Lawrence Carin† †

Google Sells A.I. for Building A.I. (Novices Welcome) – The New York Times

$GOOG Sells AI for Building #AI
https://www.NYTimes.com/2018/01/17/technology/google-sells-ai.html QT: “Humans must label the data before the system can
learn…once images…labeled…[it] operates w/o human
involvement…It can build a model from scratch.” How can one preview this? Will it be integrated into gphotos?

Initially, Google will open this service only to a small group of businesses.

But sometimes, there is no substitute for good old human labor. With Google’s new service, humans must label the data before the system can learn from it. …

Google says that once images are labeled, its new service operates without human involvement….Given more time, it
can build a model from scratch, specifically for the problem at hand.

If you are a zoologist who wants an algorithm that identifies jaguars and giraffes, said Fei-Fei Li, chief scientist inside the Google cloud group, all you have to do is supply the right images. “You upload jaguars and giraffes,” she said. “And you are done.”

Thoughts on Posting for Articles & Jclubs

Repost, using ((( for left angle brace
and ))) for right angle brace

Also, use send an email to post AT gersteinlab DOT org
(need to send to post, in addition to all).

Use plain text formatting – including for the URLs.

with the following tags & subjects for relevant jclub & article posts

1) Journal clubs

subject: Journal Club by MG on “Methylation from Environmental Toxins Causes DNA Knots & Protein Coils,” Nurture
((( tags scilit,jclub,MG,fromjclub )))

2) general article & news posts

((( tags scilit ))) for scientific literature
((( tags scinews ))) for scientific news