WIT is one of my favorite (if not *the* favorite) program in the theory community. Many in our community share my enthusiasm (and theory groups fight for the honor of hosting these meetings). The reactions from past participants leave no room for doubt – this is an important a great and experience. So if you fit the workshop’s qualifications – please do yourself a favor and apply!

The Women in Theory (WIT) Workshop is intended for graduate and exceptional undergraduate students in the area of theory of computer science. The workshop will feature technical talks and tutorials by senior and junior women in the field, as well as social events and activities. The motivation for the workshop is twofold. The first goal is to deliver an invigorating educational program; the second is to bring together theory women students from different departments and foster a sense of kinship and camaraderie.

The 7th WIT workshop will take place at Simons Institute at Berkeley, Jun 16 – 19, 2020.

**Confirmed Speakers**: Michal Feldman (Tel-Aviv University), Shafi Goldwasser (Simons, UC Berkeley)

**Organizers**: Tal Rabin (IBM), Shubhangi Saraf (Rutgers) and Lisa Zhang (Bell Labs).

**Local Host Institution: **Simons Institute at Berkeley.

**Local Arrangements**:

**Special Guest:** Omer Reingold (Stanford).

**Contact us:** womenintheory2020@gmail.com.

**To apply**: click here.

**Important dates:**

**Application deadline: **Feb 7, 2020

**Notification of acceptance: **March 15, 2020

**Workshop: **June 16-19, 2020.

One way to try to circumvent the computational barriers is by approximation algorithms (see my blog post). A different approach is to go with quantum algorithms: Grover’s search can solve NC-SAT in time. Even those of us less skeptic than Gil Kalai can probably agree that quadratic quantum speedups won’t be practical anytime soon. But in theory, I find the question of whether we can design subquadratic quantum algorithms for edit distance very interesting (see also [BEG+18]).

Alas, even with the power of quantum computers we don’t know any truly subquadratic algorithms for computing LCS/ED. On the other hand, it is not clear how to rule out even linear-time algorithms. A few weeks ago, Buhrman, Patro, and Speelman, posted a paper that gives a quantum *query complexity *lower bound for LCS/ED.

Open Problem: Close the vs gap for quantum query complexity of ED/LCS.

What is “query complexity” of ED/LCS? Buhrman et al. consider the following query model: In LCS, we want a **maximum monotone matching** between the characters of the two strings, where we can match two characters if they’re identical. Now suppose that in the query complexity problem we still want to find a maximum monotone matching, but instead of the character-equality graph (which is a union of disjoint cliques), we have an arbitrary bipartite graph, and **given a pair of vertices, the oracle tells you if there is an edge between them**.

This model may seem a bit counter-intuitive at first since the graphs may not correspond to any pair of strings; and indeed other models have been considered before [UAH76][AKO10]. But it turns out that this model is well-motivated by the NC-SETH lower bound (see discussion below).

What does the query complexity lower bound mean for algorithms on actual strings? Instead of a black box oracle, our algorithms have access to an NC-circuit that implements it. Intuitively, we don’t know how to do very much with white box circuits, so it seems plausible to hypothesize that the running time will be lower bound by the query complexity. In some sense, this is a special case of the following *ultimate hardness hypothesis *that unifies a lot of the computational hardness assumptions that we like to assume but have no idea how to prove (e.g. P!=NP, P!=BQP, NC-SETH, FP!=PPAD, etc):

[Ultimate Hardness Hypothesis] For every problem, the white-box computational complexity is lower bounded by the black-box query complexity.”

In communication complexity similar statements are known and are called simulation/lifting theorems (see e.g. Mika’s thesis). For computational complexity, there are obvious counter examples such as “decide if the oracle can be implemented by a small circuit”. So it only makes sense to continue to assume the ultimate hardness hypothesis for “reasonable problems” instead of “every problem”.

But Burhman et al. identify the following variant of the ultimate hardness hypothesis which I find very interesting. It is defined with respect to a function which takes as input the truth-table of a circuit and outputs True or False. Roughly, they hypothesize that:

[Burhman et al.-QSETH, paraphrased] For

every, deciding if is true or false is as hard whether we’re given the actual circuit, or only the guarantee that the oracle is implemented by a small circuit”

At a first read, I thought that arguments a-la impossibility of obfuscation [BGI+01] should refute this hypothesis, but a few weeks later I still don’t know how to prove it. Do you?

During my postdoc, I worked on the quantum query complexity of ED/LCS with Shalev Ben-David, Rolando La Placa, and John Wright. I was a bit bummed to find out that we got scooped by Buhrman et al, but I know of at least 3 other groups that were also scooped by the same paper, so at least we’re in good company

At the time, a fellow postdoc from Psychology asked me what I was working on. I resisted the temptation to try to explain the various quantum variants of NC-SETH, and instead told him I was working on “DNA sequencing with quantum computers”. His reaction was priceless. Regardless of what you’re actually working on, try this line during the holidays when your relatives ask you about your work.

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Applications will be accepted until the positions are filled, but review of applicants will begin after Dec 15.

Website: https://academicjobsonline.org/ajo/jobs/15578

Email: theory.stanford@gmail.com

**Parking**

There are **35** reserved spaces in **Tresidder Lot (L-39)** on **November 15, 2019. Our ** space numbers will be **14-48**; see map for location. Posted signs to read **Reserved for ****TOCA-SV CS Workshop****.**

**To avoid a citation, vehicle information is required to obtain permission to park in the designated reserved area. Use: **https://stanford.nupark.com/v2/portal/eventregister/5201e8f7-9339-4acf-8416-62f137dbc523 See instructions.

**Internet browser Chrome or Firefox are recommended and most compatible with the system.*

We prove bounds on the generalization error of convolutional networks. The bounds are characterized in terms of the training loss, the number of parameters, the Lipschitz constant of the loss, and the distance of the initial and final weights. The bounds are independent of the number of pixels in the input, as well as the width and height of hidden feature maps. These are the first bounds for DNNs with such guarantees. We present experiments with CIFAR-10, varying hyperparameters of a deep convolutional network, comparing our bounds with practical generalization gaps.

- Dean Doron, Stanford University,

Existing techniques for derandomizing algorithms based on circuit lower bounds yield a large polynomial slowdown in running time. We show that assuming exponential lower bounds against nondeterministic circuits, we can convert any randomized algorithm running in time T to a deterministic one running in time nearly T^2. Under complexity-theoretic assumptions, such a slowdown is nearly optimal.

In this talk I will concentrate on the role of error-correcting codes in those techniques. We will see which properties of error-correcting codes are useful for constructing pseudorandomness primitives sufficient for derandomization, where they came short of achieving better slowdown, and how we can overcome that.

Based on joint work with Dana Moshkovitz, Justin Oh and David Zuckerman

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The call for papers for FORC 2020 is out. The PC chair, Aaron Roth, has done a remarkable job forming a strong program committee, and we are off to a great start. Please consider sending your research papers and looking forward to seeing many of you at FORC 2020 in the beginning of June at Harvard.

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Yael Kalai, Matt Weinberg, and I are organizing a TCS mentoring workshop in upcoming FOCS with a focus on **demystifying the job market**.

The program includes a senior panel featuring Shafi Goldwasser, Samir Khuller, Tim Roughgarden, and Eva Tardos, a junior panel starring Inbal Talgam-Cohen, Omri Weinstein, and Henry Yuen, and two exemplary job talks by Eshan Chattopadhyay and Pravesh Kothari.

Visit our website to see the full program and most importantly suggest panel questions.

Amir Abboud and I are organizing a workshop on fine-grained complexity, to be held Jan 2nd 2020 at Tel-Aviv University, closing the first annual TAU Theory-Fest.

The program includes a morning of plenary talks (Karl Bringmann, Seth Pettie, and Barna Saha) and shorter cutting-edge technical talks in the afternoon.

(If you have something interesting to share with the fine-grained complexity community, and we haven’t contacted you yet about giving a talk, please let us know.)

Looking forward to seeing you in Baltimore and Tel-Aviv!

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Deal friends,

We are happy to announce the birth of a new conference on Information-Theoretic Cryptography (ITC). Information-theoretic cryptography studies security in the presence of computationally unbounded adversaries and covers a wide array of topics at the intersection of cryptography, coding theory, information-theory and theory of computation. Notable examples include randomness extraction and privacy amplification, secret sharing, secure multiparty computation and proof systems, private-information retrieval and locally decodable codes, authentication codes and non-malleable codes, differential privacy, quantum information processing, and information-theoretic foundations of physical-layer security. See https://itcrypto.github.io for more information.

ITC replaces the International Conference on Information Theoretic Security (ICITS), which was dedicated to the same topic and ran 2005-2017. ITC can be seen as a reboot of ICITS with a new name, a new steering committee and a renewed excitement. (beware: there is a fake website for ICITS 2019 created by a known fraudulent organization)

The conference will have two tracks: a conference track and a “greatest hits” track. The conference track will operate like a traditional conference with the usual review process and published proceedings. The “greatest hits” track consists of invited talks (not included in the proceedings) that highlight the most exciting recent advances in the area. We solicit nominations for “greatest hits” talks from the community.

The first ITC conference will take place in Boston, MA on June 17-19, 2020 (just before STOC). The submission deadline for ITC 2020 is Dec 16, 2019 and the call for papers (including a nomination procedure for the greatest hits track) is available here: https://itcrypto.github.io/2020.html

Please submit your best work to ITC 2020! We hope to see many of you there!

best regards,

The Steering Committee: Benny Applebaum (Chair), Ivan Damgård , Yevgeniy Dodis, Yuval Ishai, Ueli Maurer, Kobbi Nissim, Krzysztof Pietrzak, Manoj Prabhakaran, Adam Smith, Yael Tauman Kalai, Stefano Tessaro, Vinod Vaikuntanathan, Hoeteck Wee, Daniel Wichs, Mary Wootters, Chaoping Xing, Moti Yung

With roughly a week left, here is a reminder that the *11 ^{th} Innovations in Theoretical Computer Science* (ITCS) submission deadline is next

For more details on the scope and specifics, please consult the CFP here; it also contains the link to the submission server. We’re looking forward to reading your excellent and innovative submissions from across TCS!

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On the Importance of Disciplinary Pride for Multidisciplinary Collaboration

I am a big fan of collaborations, even if they come with their own challenges. I always got further and enjoyed research much more because of my collaborators. I’m forever indebted to so many colleagues and dear, dear friends. Each and every one of them was better than me in some ways. To contribute, I had to remember my own strengths and bring them to the table. The premise of this post is that the same holds for collaboration between fields. It should be read as a call for theoreticians to bring the tools and the powerful way of thinking of TOC into collaborations. We shouldn’t be blind to the limitation of our field but obsessing on those limitations is misguided and would only limit our impact. Instead we should bring our best and trust on the other disciplines we collaborate with to do the same (allowing each to complement and compensate for the other).

The context in which these thoughts came to my mind is Algorithmic Fairness. In this and other areas on the interface between society and computing, true collaboration is vital. Not surprisingly, attending multidisciplinary programs on Algorithm Fairness, is a major part of my professional activities these days. And I love it – I get to learn so much from people and disciplines that have been thinking about fairness for many decades and centuries. In addition, the Humanities are simply splendid. Multidisciplinary collaborations come with even more challenges than other collaborations: the language, tools and perspectives are different. But for exactly the same reasons they can be even more rewarding. Nevertheless, my fear and the reason for this post is that my less experienced TOC colleagues might come out from those interdisciplinary meetings frustrated and might lose confidence in what TOC can contribute. It feels to me that old lessons about the value of TOC need to be learned again. There is a lot to be proud of, and holding to this pride would in fact make us better collaborators not worse.

In the context of Algorithmic Fairness, we should definitely acknowledge (as we often do) that science exists within political structures, that algorithms are not objective and that mathematical definitions cannot replace social norms as expressed by policy makers. But let’s not take these as excuses for inaction and let’s not withdraw to the role of spectators. In this era of algorithms, other disciplines need us just as much as we need them .

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**tl;dr:** the ITCS’20 CFP has been posted. Read it, and submit your work there!

We invite you to submit your papers to the 11th Innovations in Theoretical Computer Science (ITCS). The conference will be held at the University of Washington in Seattle, Washington from January 12-14, 2020.

ITCS seeks to promote research that carries a strong conceptual message (e.g., introducing a new concept, model or understanding, opening a new line of inquiry within traditional or interdisciplinary areas, introducing new mathematical techniques and methodologies, or new applications of known techniques). ITCS welcomes both conceptual and technical contributions whose contents will advance and inspire the

greater theory community.

**Important dates**

*Submission deadline:*September 9, 2019 (05:59pm PDT)*Notification to authors:*October 31, 2019*Conference dates:*January 12-14, 2020

See the website at http://itcs-conf.org/itcs20/itcs20-cfp.html for detailed information regarding submissions.

**Program committee**

Nikhil Bansal, CWI + TU Eindhoven

Nir Bitansky, Tel-Aviv University

Clement Canonne, Stanford

Timothy Chan, University of Ilinois at Urbana-Champaign

Edith Cohen, Google and Tel-Aviv University

Shaddin Dughmi, University of Southern California

Sumegha Garg, Princeton

Ankit Garg, Microsoft research

Ran Gelles, Bar-Ilan University

Elena Grigorescu, Purdue

Tom Gur, University of Warwick

Sandy Irani, UC Irvine

Dakshita Khurana, University of Illinois at Urbana-Champaign

Antonina Kolokolova, Memorial University of Newfoundland.

Pravesh Kothari, Carnegie Mellon University

Rasmus Kyng, Harvard

Katrina Ligett, Hebrew University

Nutan Limaye, IIT Bombay

Pasin Manurangsi, UC Berkeley

Tamara Mchedlidze, Karlsruhe Institute of Technology

Dana Moshkovitz, UT Austin

Jelani Nelson, UC Berkeley

Merav Parter, Weizmann Institute

Krzysztof Pietrzak, IST Austria

Elaine Shi, Cornell

Piyush Srivastava, Tata Institute of Fundamental Research, Mumbai

Li-Yang Tan, Stanford

Madhur Tulsiani, TTIC

Gregory Valiant, Stanford

Thomas Vidick, California Institute of Technology (chair)

Virginia Vassilevska Williams, MIT

Ronald de Wolf, CWI and University of Amsterdam

David Woodruff, Carnegie Mellon University