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#theoreticalComputerScience

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Clément Canonne

This Karp Distinguished Lecture at at the Simons Institute by Rocco Servedio on July 10 on "New Directions in Property Testing" looks exciting! Rocco is a fantastic speaker.
simons.berkeley.edu/events/new

The Karp Lectures are public lectures, meant for a broad, general #TheoreticalComputerScience audience. Registration is free, in person or online.

To check your time zone: timeanddate.com/worldclock/con

Simons Institute for the Theory of ComputingNew Directions in Property Testing | Richard M. Karp Distinguished LectureProperty testing algorithms seek to determine whether an unknown massive object has some particular property of interest, or is "far" from having the property, while inspecting only a tiny portion of the object. Recent years have witnessed significant progress on both classic property testing problems and the development of several new property testing problems and frameworks, motivated by connections to machine learning theory and high-dimensional data analysis. In this talk, Rocco Servedio will survey several of these new property testing problems, models, and results. Rocco Servedio received his undergraduate degree in mathematics at Harvard and his PhD in computer science at Harvard, where his thesis was advised by Leslie Valiant. Servedio is a professor of computer science at Columbia University, where he has received a Presidential Teaching Award and served as department chair. His research interests within theoretical computer science include computational learning theory, property testing, computational complexity theory, lower bounds, pseudorandomness, and the study of randomness in computing. He has served as PC chair of conferences and workshops including STOC, CCC, COLT, and RANDOM, and has received best paper and best student paper awards from STOC, FOCS, COLT, ALT, and CCC.   The Richard M. Karp Distinguished Lectures were created in Fall 2019 to celebrate the role of Simons Institute Founding Director Dick Karp in establishing the field of theoretical computer science, formulating its central problems, and contributing stunning results in the areas of computational complexity and algorithms. Formerly known as the Simons Institute Open Lectures, the series features visionary leaders in the field of theoretical computer science and is geared toward a broad scientific audience. Light refreshments will be available at 3 p.m., prior to the start of the lecture.  The lecture recording URL will be emailed to registered participants. This URL can be used for immediate access to the livestream and recorded lecture. Lecture recordings will be publicly available on SimonsTV about 12 to 15 days following each presentation unless otherwise noted. The Simons Institute regularly captures photos and video of activity around the Institute for use in publications and promotional materials.  If you require special accommodation, please contact our access coordinator at simonsevents [at] berkeley.edu with as much advance notice as possible.
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Clément Canonne

📢 Next week (Wed 12/13) on TCS+: at 10am PT/1pm ET, Aaron Bernstein from Rutgers University will speak on "Negative-Weight Single-Source Shortest Paths in Near-linear Time." Join us for the last TCS+ talk of 2023! #Algorithms #TheoreticalComputerScience

Details: tcsplus.wordpress.com/2023/12/

Register (optional): docs.google.com/forms/d/e/1FAI

TCS+ · TCS+ talk: Wednesday, December 13 — Aaron Bernstein, Rutgers UniversityThe next TCS+ talk (and the last of 2023!) will take place this coming Wednesday, December 13th at 1:00 PM Eastern Time (10:00 AM Pacific Time, 19:00 Central European Time, 18:00 UTC). Aaron Bernst…
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Ross Gayler

Here's a really interesting (long) paper on what a theory of computing based on arbitrary physical substrates might look like: arxiv.org/abs/2307.15408

"Toward a formal theory for computing machines made out of whatever physics offers: extended version"

Herbert Jaeger, Beatriz Noheda, Wilfred G. van der Wiel (2023)

@bnoheda

arXiv.orgToward a formal theory for computing machines made out of whatever physics offers: extended versionApproaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to systematically engineer computing systems that are based on unconventional physical effects, we need guidance from a formal theory that is different from the symbolic-algorithmic theory of today's computer science textbooks. We propose a general strategy for developing such a theory, and within that general view, a specific approach that we call "fluent computing". In contrast to Turing, who modeled computing processes from a top-down perspective as symbolic reasoning, we adopt the scientific paradigm of physics and model physical computing systems bottom-up by formalizing what can ultimately be measured in any physical substrate. This leads to an understanding of computing as the structuring of processes, while classical models of computing systems describe the processing of structures.
#NewPaper#TheoreticalComputerScience#neuromorphic
Clément Canonne

ICYMI, there's been a series of online talks on "adversarially robust streaming #algorithms" on the Foundations of #DataScience virtual seminar series. The first 3 recordings are available:
sites.google.com/view/dstheory

David Woodruff on "Adversarially Robust Streaming Algorithms"

Edith Cohen "On Robustness to Adaptive Inputs: A Case Study of CountSketch"

Omri Ben-Eliezer on "Robust sampling and online learning"

(one or two more to come this semester!) #TheoreticalComputerScience #TCS #talks

sites.google.comVirtual Talk Series Dec 14, 2022: Omri Ben-Eliezer (MIT) "Robust sampling and online learning"
Clément Canonne

Hey, that seems cool!* Zero-Knowledge proofs in the streaming setting (verifier has limited working memory, gets one pass over the input).
arxiv.org/abs/2301.02161
By Cormode, Dall’Agnol, @tomgur, and Hickey. #TCS #arXiv #TheoreticalComputerScience

* Except for the default bright green color of the links, that is :)

arXiv.orgStreaming Zero-Knowledge ProofsWe initiate the study of zero-knowledge proofs for data streams. Streaming interactive proofs (SIPs) are well-studied protocols whereby a space-bounded algorithm with one-pass access to a massive stream of data communicates with a powerful but untrusted prover to verify a computation that requires large space. We define the notion of zero-knowledge in the streaming setting and construct zero-knowledge SIPs for the two main building blocks in the streaming interactive proofs literature: the sumcheck and polynomial evaluation protocols. To the best of our knowledge all known streaming interactive proofs are based on either of these tools, and indeed, this allows us to obtain zero-knowledge SIPs for central streaming problems such as index, frequency moments, and inner product. Our protocols are efficient in terms of time and space, as well as communication: the space complexity is $\mathrm{polylog}(n)$ and, after a non-interactive setup that uses a random string of near-linear length, the remaining parameters are $n^{o(1)}$. En route, we develop a toolkit for designing zero-knowledge data stream protocols, consisting of an algebraic streaming commitment protocol and a temporal commitment protocol. The analysis of our protocols relies on delicate algebraic and information-theoretic arguments and reductions from average-case communication complexity.
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