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CS Colloquium (18/11): Yonina Eldar (Weizmann Institute of Science)
by Amir Gilad 12 Nov '24

12 Nov '24

Dear all, Next week, we have the pleasure of hosting Prof. Yonina Eldar (Weizmann Institute of Science) at our CS colloquium. The title and abstract of the talk, as well as a short bio of the speaker appear below. The seminar will be held on Monday, November 18th at 14:00 (refreshments at 13:45). *Location*: Romm C220, Rothberg Building. Looking forward to seeing you, Amir and Moshe =============================== *Speaker: *Prof. Yonina Eldar <https://www.weizmann.ac.il/math/yonina/> (Weizmann Institute of Science) *Title*: Model Based Deep Learning: Applications to Imaging and Communication *Abstract*: Deep neural networks provide unprecedented performance gains in many real-world problems in signal and image processing. Despite these gains, the future development and practical deployment of deep networks are hindered by their black-box nature, i.e., a lack of interpretability and the need for very large training sets. On the other hand, signal processing and communications have traditionally relied on classical statistical modeling techniques that utilize mathematical formulations representing the underlying physics, prior information and additional domain knowledge. Simple classical models are useful but sensitive to inaccuracies and may lead to poor performance when real systems display complex or dynamic behaviour. Here we introduce various approaches to model based learning which merge parametric models with optimization tools and classical algorithms leading to efficient, interpretable networks from reasonably sized training sets. We will consider examples of such model-based deep networks to image deblurring, image separation, super resolution in ultrasound and microscopy, radar for clinical applications, efficient communication systems, and more. *Bio: *Yonina Eldar is a Professor in the Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel where she heads the center for Biomedical Engineering and Signal Processing and holds the Dorothy and Patrick Gorman Professorial Chair. She is also a Visiting Professor at MIT, a Visiting Scientist at the Broad Institute, and an Adjunct Professor at Duke University and was a Visiting Professor at Stanford. She is a member of the Israel Academy of Sciences and Humanities, an IEEE Fellow and a EURASIP Fellow. She received the B.Sc. degree in physics and the B.Sc. degree in electrical engineering from Tel-Aviv University, and the Ph.D. degree in electrical engineering and computer science from MIT, in 2002. She has received many awards for excellence in research and teaching, including the IEEE Signal Processing Society Technical Achievement Award (2013), the IEEE/AESS Fred Nathanson Memorial Radar Award (2014) and the IEEE Kiyo Tomiyasu Award (2016). She was a Horev Fellow of the Leaders in Science and Technology program at the Technion and an Alon Fellow. She received the Michael Bruno Memorial Award from the Rothschild Foundation, the Weizmann Prize for Exact Sciences, the Wolf Foundation Krill Prize for Excellence in Scientific Research, the Henry Taub Prize for Excellence in Research (twice), the Hershel Rich Innovation Award (three times), and the Award for Women with Distinguished Contributions. She received several best paper awards and best demo awards together with her research students and colleagues, was selected as one of the 50 most influential women in Israel, and was a member of the Israel Committee for Higher Education. She is the Editor in Chief of Foundations and Trends in Signal Processing, a member of several IEEE Technical Committees and Award Committees, and heads the Committee for Promoting Gender Fairness in Higher Education Institutions in Israel.

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CS Colloquium (11/11): Elad Hazan (Princeton University)
by Moshe Babaioff 10 Nov '24

10 Nov '24

Dear all, Next week, we have the pleasure of hosting *Prof. Elad Hazan* (Princeton University) at our CS colloquium. The title and abstract of the talk appear below. For bio see here <https://www.ehazan.com/bio/>. The seminar will be held on Monday, November 11th at 14:00. (Refreshments at 13:45) *Location*: Romm C220, Rothberg Building. Looking forward to seeing you, Amir and Moshe =============================== *Speaker: **Prof. Elad Hazan <https://www.ehazan.com/bio/>* (Princeton University) *Title*: Spectral Transformers *Abstract*: We'll discuss a new technique for sequence modeling for prediction tasks with long range dependencies and fast inference/generation. At the heart of the method is a new formulation for state space models (SSMs) based on learning linear dynamical systems with the spectral filtering algorithm. This gives rise to a novel sequence prediction architecture we call a spectral state space model. Spectral state space models have two primary advantages. First, they have provable robustness properties as their performance depends on neither the spectrum of the underlying dynamics nor the dimensionality of the problem. Second, these models are constructed with fixed convolutional filters that do not require learning while still outperforming SSMs in both theory and practice. The resulting models are evaluated on synthetic dynamical systems as well as long-range prediction tasks of various modalities. These evaluations support the theoretical benefits of spectral filtering for tasks requiring very long range memory. The talk will be self-contained, but here is a link to more information about spectral transformers and filtering <https://sites.google.com/view/gbrainprinceton/projects/spectral-transformers>.

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CS Colloquium (4/11): Avi Wigderson (IAS)
by Moshe Babaioff 04 Nov '24

04 Nov '24

Dear all, Next week, we have the pleasure of hosting *Prof. Avi Wigderson* (IAS), the recipient of the 2023 ACM A.M. Turing Award <https://awards.acm.org/award-recipients/wigderson_3844537>, at our CS colloquium. The seminar will be held on Monday, November 4th at 14:00. (Refreshments at 13:45) *Location*: Auditorium, Rothberg Building (Note the unusual location) The title and abstract appear below (and a short bio is attached). Looking forward to seeing you, Amir and Moshe =============================== *Title*: Reading Alan Turing *Abstract*: I will discuss some well-known and less-known papers of Turing, demonstrate the scope of deep, prescient ideas he put forth, and mention follow-up bodies of work on these ideas by the Theoretical CS community. [image: Avi Wigderson.png]

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Fwd: Turing Minds (Jewish student initiative)
by Amir Gilad 09 Oct '24

09 Oct '24

Dear all, Please see this email about an informative speaker series at Georgia Tech featuring many interesting talks. Best, Amir Begin forwarded message: *From:* "Axel, Zachary N" <zaxel3(a)gatech.edu> *Date:* September 29, 2024 at 5:33:58 AM GMT+3 *To:* "Axel, Zachary N" <zaxel3(a)gatech.edu> *Subject:* *Turing Minds (Jewish student initiative)* Dear Esteemed HUJI faculty, I hope this email finds you well. My name is Zack Axel, and I am a proud Jewish Georgia tech Masters in CS student who is spearheading a virtual intiative featuring many Turing award winners and even some notable programming language creators. It would be an absolute honor if HUJI students and faculty in Israel could attend the series virtually. It comes after we had an informative series last year, with *5 *other Turing winners; incl. Leslie Lamport, Ed Feigenbaum, Barbara Liskov, Jeff Ullman, Jack Dongarra: *https://www.atlantajewishtimes.com/ga-tech-students-lead-speaker-series/ <https://www.atlantajewishtimes.com/ga-tech-students-lead-speaker-series/>* It is free for anyone to attend these speaker events(I invite anyone at your CS departments who wishes to attend) , and we hope to educate the greater community on the contributions of these awesome computer scientists. Our first speaker starts 10/4. We will host 9:* Donald Knuth, Geoffrey Hinton, Vint Cerf, James Gosling, Leslie Valiant, Joseph Sifakis, Yoshua Bengio, John Hennessey, Avi Wigderson, Michael Stonebraker*, and more. The RSVP website, in case anyone is interested in tuning in from your CS departments, is *www.turing.rsvp <http://www.turing.rsvp/>** . * *Can you please reply to me if your students and faculty would be interested in attending this? I sincerely hope this is a value add and informative/highly educational experience to all. * My love to Israel, Zack Axel, Georgia tech Computer Science Events Chair

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Celebrating the Science of Yoram Singer
by Sagie Benaim 08 Sep '24

08 Sep '24

Dear all, The following may be of interest. Link for registration: https://forms.gle/6nXsAgNYkVGtnQgZ6 [image: image001.png]

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CS Colloquium (22/07): Yohai Bar-Sinai (Tel Aviv University)
by Sagie Benaim 22 Jul '24

22 Jul '24

Dear all, Next week, we have the pleasure of having Dr. Yohai Bar-Sinai give a talk in the colloquium. The seminar will be held on Monday, July 22nd at 14:00. Location: C221. The title and abstract appear below. Looking forward to seeing you, Sagie and Liat *Title:* Grokking as a near-critical phenomenon *Abstract:* The empirical success of neural models far surpasses their theoretical understanding, and explaining their inner workings is important both for practical reasons and as a fundamental scientific question. In this talk we will focus on an intriguing phenomenon, grokking, in which a neural model learns to generalize long after it has completely fit the training data. This sharp transition between memorization and generalization has been observed in various synthetic and realistic scenarios. We study grokking in simplified settings of linear or almost linear models, both in regression and classification. Using tools from statistical mechanics, random matrix theory and optimization, we show analytically and numerically that some observations of grokking are linked to the existence of a phase transition, or singularity in the long-time dynamics of training. In particular, we show that the delayed generalization is a result of slow dynamical time scales, which generically appear in the vicinity of phase transitions, a phenomenon known in the physical literature as "critical slowing down". This allows us to derive concrete scaling predictions about how grokking time depends on dimensionality, dataset size, and regularization, predictions which apply also for more complicated scenarios due to the universal properties of criticality. *Short Bio:* Yohai Bar-Sinai is a senior lecturer in the School of Physics in Tel-Aviv University. Before joining TAU in 2020, he conducted postdoctoral research in the Department of Applied Mathematics at Harvard, supported by the McDonnell Postdoctoral Fellowship, and then spent two years at Google Research (Israel). He holds a Bachelor's degree in Math and Physics from HUJI, a Master's degree from ENS and UPMC universities in Paris (FPGG scholarship) , and a PhD in theoretical physics from the Weizmann Institute. His interdisciplinary research focuses on using statistical physics, computational physics, and machine learning to investigate complex non-linear phenomena.

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CS Colloquium (15/07): Yuval Rabani (Hebrew University)
by Sagie Benaim 15 Jul '24

15 Jul '24

Dear all, Next week, we have the pleasure of having Prof. Yuval Rabani give a talk in the colloquium. The seminar will be held on Monday, July 15th at 14:00. Location: C221. The title and abstract appear below. Looking forward to seeing you, Sagie and Liat *Title:* Diversity in evolutionary dynamics *Abstract:* We consider the dynamics imposed by natural selection on the populations of two competing, sexually reproducing, haploid species. In this setting, the fitness of any genome varies over time due to the changing population mix of the competing species; crucially, this fitness variation arises naturally from the model itself, without the need for imposing it exogenously as is typically the case. Previous work on this model (Piliouras and Schulman, 2018) showed that, in the special case where each of the two species exhibits just two phenotypes, genetic diversity is maintained at all times. This finding supported the tenet that sexual reproduction is advantageous because it promotes diversity, which increases the survivability of a species. In the present paper we consider the more realistic case where there are more than two phenotypes available to each species. The conclusions about diversity in general turn out to be very different from the two-phenotype case. Our first result is negative: namely, we show that sexual reproduction does not guarantee the maintenance of diversity at all times, i.e., the result of Piliouras and Schulman does not generalize. Our counterexample consists of two competing species with just three phenotypes each. We show that, for any time t0 and any ε > 0, there is a time t ≥ t0 at which the combined diversity of both species is smaller than ε. Our main result is a complementary positive statement, which says that in any non-degenerate example, diversity is maintained in a weaker, “infinitely often” sense. Thus, our results refute the supposition that sexual reproduction ensures diversity at all times, but affirm a weaker assertion that extended periods of high diversity are necessarily a recurrent event. Joint work with Leonard J. Schulman and Alistair Sinclair

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CS Colloquium (08/07): Ariel Goldstein (Hebrew University)
by Sagie Benaim 04 Jul '24

04 Jul '24

Dear all, Next week, we have the pleasure of having Prof. Ariel Goldstein give a talk in the colloquium. The seminar will be held on Monday, July 8th at 14:00. Location: C221. The title, abstract and bio appear below. Looking forward to seeing you, Sagie and Liat *Title:* Deep Modeling as (more) Than (just) Cognitive Framework *Abstract:* In my presentation, I will explore the assertion that deep learning-based models are not mere black boxes but rather valid frameworks for articulating computational theories for cognition and their neural infrastructure. My focus will primarily be on the comprehension and production of natural speech, using naturalistic stimuli and unrestrained conversations. I will illustrate common principles shared between deep language models (text-based), deep multimodal models (text and audio-based), and the brain using the neural activity associated with speech. I will discuss the new light shed by adopting deep modeling of fundamental long-lasting issues in cognitive neuroscience. In addition I will discuss the interplay between computer science, brain science and psychology and some of the ways they influence each other. *Bio*: Ariel Goldstein is faculty member specializing in the cognition department and business school at the Hebrew University. He holds bachelor's degrees in mathematics from Bar-Ilan University and psychology from the Open University. Ariel completed his master's and PhD at the Hebrew University, focusing on high-level nonconscious cognition. He did his postdoctoral fellowship at Princeton, where he worked on integrating deep learning models with human neural activity. He leads a lab that explores universal principles governing meaningful interactions, developing a novel triangular framework for understanding human-to-human, human-to-model, and model-to-model interactions.

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CS Colloquium (01/07): Yael Amsterdamer (Bar-Ilan University)
by Sagie Benaim 01 Jul '24

01 Jul '24

Dear all, Next week, we have the pleasure of having Prof. Yael Amsterdamer give a talk in the colloquium. The seminar will be held on Monday, July 1st at 14:00. Location: C221. The title, abstract and bio appear below. Looking forward to seeing you, Sagie and Liat *Title:* Active Data Cleaning *Abstract:* We take an active approach to the cleaning of uncertain databases, by proposing a set of tools to guide the cleaning process. We start with a database whose tuple correctness is uncertain, and with some means of resolving this uncertainty, e.g., crowdsourcing, experts, a trained ML model or external sources. Guided by a query that defines what part of the data is of importance, our goal is to select tuples whose cleaning would effectively resolve uncertainty in query results. In other words, we develop a query-guided process for the resolution of uncertain data. Our approach combines techniques from different fields, including the use of provenance information to capture the propagation of errors to query results, Boolean interactive evaluation to decide which input tuples to clean based on their role in output derivation, and active learning to estimate the probability of errors. *Bio*: Yael Amsterdamer is a Professor at the Department of Computer Science, Bar-Ilan University, and the head of the Data Management Lab. She received her Ph.D. in Computer Science from Tel-Aviv University, and has been a visiting Scholar at the University of Pennsylvania, Philadelphia, PA and jointly at Télécom Paris and INRIA institute (Paris, France). Her research is in the field of interactive data management spanning topics such as crowd-powered data management, interactive summarization and data cleaning. Her research was awarded multiple competitive grants including the Israeli Science Foundation (ISF) personal grants, the Israeli Ministry of Science (MOST) grant, and the BIU Center for Research in Applied Cryptography and Cyber Security Personal Grant. Her research is published in top venues of her field and she continually serves in roles such as area chair and demo track chair for ICDE, DEI chair for SIGMOD, PC chair for aiDM and others.

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CS Colloquium (24/06): Yannai A. Gonczarowski (Harvard University)
by Sagie Benaim 24 Jun '24

24 Jun '24

Dear all, Next week, we have the pleasure of having Prof. Yannai A. Gonczarowski give a talk in the colloquium. The seminar will be held on Monday, June 24th at 14:00. Location: C221. The title, abstract and bio appear below. Looking forward to seeing you, Sagie and Liat *Title:* Strategyproofness-Exposing Mechanism Descriptions *Abstract:* A menu description presents a mechanism to player i in two steps. Step (1) uses the reports of other players to describe i's menu: the set of i's potential outcomes. Step (2) uses i's report to select i's favorite outcome from her menu. Can menu descriptions better expose strategyproofness, without sacrificing simplicity? We propose a new, simple menu description of Deferred Acceptance. We prove that—in contrast with other common matching mechanisms—this menu description must differ substantially from the corresponding traditional description. We demonstrate, with an incentivized lab experiment, the promise and challenges of menu descriptions. Based upon joint works with Ori Heffetz, Guy Ishai, and Clayton Thomas. *Bio*: Yannai A. Gonczarowski is an Assistant Professor of Economics and of Computer Science at Harvard University—the first faculty member at Harvard to have been appointed to both of these departments. Interested in both economic theory and theoretical computer science, Yannai explores computer-science-inspired economics: he harnesses approaches, aesthetics, and techniques traditionally originating in computer science to derive economically meaningful insights. Yannai received his PhD from the Departments of Mathematics and Computer Science, and the Center for the Study of Rationality, at the Hebrew University of Jerusalem. Yannai is also a professionally-trained opera singer, having acquired a bachelor’s degree and a master’s degree in Classical Singing at the Jerusalem Academy of Music and Dance. Yannai's doctoral dissertation was recognized with several awards, including the Michael B. Maschler Prize of the Israeli Chapter of the Game Theory Society and the ACM SIGecom Doctoral Dissertation Award. For the design and implementation of the National Matching System for Gap-Year Programs in Israel, he was awarded the inaugural INFORMS AMD Michael H. Rothkopf Junior Researcher Paper Prize (first place). Yannai was also the recipient of the inaugural ACM SIGecom Award for Best Presentation by a Student or Postdoctoral Researcher. His first textbook, "Mathematical Logic through Python" (Gonczarowski and Nisan), which introduces a new approach to teaching the material of a basic Logic course to Computer Science students, tailored to the unique intuitions and strengths of this cohort of students, was published by Cambridge University Press.

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