July 2024 - Colo - huji-cs listserver

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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