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NLP session at AI Week – featuring talks by Prof. Yoav Goldberg and Prof. Ido Dagan

Keynote Yoav Goldberg ,  Research Director of AI2 Israel; Professor at the Computer Science Department, Bar-Ilan University 11:05 - 11:25  Calendar 1  Calendar Beyond End-to-End: the Case of Multi-text Summarization Ido Dagan ,  Professor at the Department of Computer Science, Bar-Ilan University; Director, Bar-Ilan Data Science Institute

Continuous vs. Discrete Optimization of Deep Neural Networks. Nadav Cohen (TAU).

On Sunday 6.3.22 12:00 we will host Nadav Cohen from Tel-Aviv University. Please see the details below. The recording of Nadav' talk: https://us02web.zoom.us/rec/share/cNPxCTCpoLjYZFQI0MMiiukHgNypjRiBkAEobfovvw-ebJzaF1r0RNDpXbfZhdIJ.wmI2PSdk1z3fGxyu?startTime=1646561098000 Title: Continuous vs. Discrete Optimization of Deep Neural Networks Abstract: Existing analyses of optimization in deep learning are either continuous, focusing on variants of gradient flow (GF), or discrete, directly treating variants ... Read more

Learning to Cooperate and Compete in Diplomacy. Dr. Noam Brown, FACEBOOK. (CS Colloquium)

Building 216 room 201

Dr. Noam Brown Will lecture on Learning to Cooperate and Compete in Diplomacy AI has made incredible progress in purely adversarial games such as chess, go, and poker. However, the real world involves a complex mixture of cooperation and competition, sometimes with irrational or suboptimal participants, and in these settings past AI techniques fall apart. For ... Read more

Deep Learning for Representation Learning by Dr. Uri Shaham Yale University (CS Colloquium)

Building 216 room 201

Dr. Uri Shaham. Yale University Will lecture on Deep Learning for Representation Learning In this talk I will present two deep learning-based algorithms for representation learning. In the first half of the talk I will present SpectralNet, a  deep learning approach for spectral clustering, which is scalable and allows for straight-forward out of sample extension.  ... Read more

Learning to Plan in the Real World – Roni Stern, Ben Gurion University

Building 216 room 201

Prof. Roni Stern, Ben Gurion University Learning to Plan in the Real World Planning is often referred to as the art of thinking before acting. As such, automated planning is a long-term goal of Artificial Intelligence (AI). Most planning algorithms in the literature are model-based, in the sense that they assume a compositional model of ... Read more

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators. Rinon Gal (TAU and NVIDIA).

Zoom: https://us02web.zoom.us/j/85784376223?pwd=VkMvdGl1YXFBMExSdC9mRnVnZjZIQT09 Meeting ID: 857 8437 6223 Passcode: 1212 Rinon Gal from Tel-Aviv university and NVIDIA. Title: StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators Abstract: Can a generative model be trained to produce images from a specific domain, guided by a text prompt only, without seeing any image? In other words: can an image generator ... Read more

Robust Android Malware Detection, Harel Berger (Ariel U.)

 The lecture will be given by  Mr. Harel Berger from Ariel University in zoom..   zoom link:  https://us02web.zoom.us/j/83383478356 Title: Robust Android Malware Detection Abstract: A growing number of malware detection methods are heavily based on Machine Learning (ML) and Deep Learning techniques. However, these classifiers are often vulnerable to evasion attacks, in which an adversary manipulates a malicious instance from being detected. This ... Read more

Solving Stochastic Programming Problems by Operator Splitting. Jonathan Eckstein, Rutgers Business School.

Conference Room Building 605, 3rd Fl. Bar-Ilan University

Solving Stochastic Programming Problems by Operator Splitting A B S T R A C T This talk describes the solution of convex optimization problems that include uncertainty modeled by a finite but potentially very large multi-stage scenario tree. In 1991, Rockafellar and Wets proposed the progressive hedging (PH) algorithm to solve such problems. This method ... Read more

Model-Based Deep Learning in Signal Processing and Communications, Dr. Nir Shlezinger (BGU)

Title: Model-Based Deep Learning in Signal Processing and Communications Abstract: Recent years have witnessed a dramatically growing interest in machine learning (ML) methods. These data-driven trainable structures have demonstrated an unprecedented empirical success in various applications, including computer vision and speech processing. The benefits of ML-driven techniques over traditional model-based approaches are twofold: First, ML ... Read more

TAU Style: inversion, editing, and applications of StyleGAN. Dr. Amit Bermano.

Building 216 room 201

Speaker: Dr. Amit Bermano from Tel-Aviv University. Title: TAU Style: inversion, editing, and applications of StyleGAN. Abstract: The generative abilities of GANs are revolutionizing the field of image synthesis and manipulation. Specifically, StyleGAN reaches the highest levels of image quality, and has become the de-facto golden standard for the editing of facial images.  StyleGAN is unsupervised, ... Read more

Computational challenges in protein-RNA interactions, Dr. Yaron Orenstein (BGU)

Building 216 room 201

Dr. Yaron Orenstein Ben-Gurion University Computational challenges in protein-RNA interactions Protein-RNA interactions play vital roles in many cellular processes, and as a result are the main focus of many biological studies. Biologists would like to efficiently measure protein-RNA interactions in high-throughput, and based on these high-throughput experimental measurements train accurate machine-learning models to predict interactions ... Read more

DeepDPM: Deep Clustering With an Unknown Number of Clusters. Meitar Ronen (Ben-Gurion University)

The recording of Meitar's talk is available: https://us02web.zoom.us/rec/share/mdFnT_lf6ct-9VRfTFhnrsEe9724KteEsl7v8I86zf19AaDtKiChgM3Ai6zxQ5CG.PcEfwNZ04_H-NsGm?startTime=1650790948000 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ On Sunday 24.4.22, at 12:00, we will host Meitar Ronen from Ben-Gurion University. Zoom: https://us02web.zoom.us/j/85784376223?pwd=VkMvdGl1YXFBMExSdC9mRnVnZjZIQT09 Meeting ID: 857 8437 6223 Passcode: 1212 Title: DeepDPM: Deep Clustering With an Unknown Number of Clusters. Abstract: Deep Learning (DL) has shown great promise in the unsupervised task of clustering. ... Read more

Tissue level insights from cellular measurements. Matan Hofree (Weizmann)

Building 216 room 201

Department of Computer Science - Bar-Ilan University Computer Science Colloquium Monday, April 25, 2022 12:00 P.M. Dr. Matan Hofree Weizmann Institute Will lecture on: Tissue level insights from cellular measurements Identifying multi-cellular hubs by co-variation analysis of single-cell expression Therapy response varies considerably among cancer patients and depends on tumor intrinsic factors and interactions with ... Read more

Label-free Domain Adaptation and Multimodal Manifold Learning with Riemannian Geometry. Ronen Talmon (Technion)

The recording of Ronen's talk is available at the following link: https://us02web.zoom.us/rec/share/CyXhXnADPm2gwEPqa4NDasRx3Zz_1DOUMR8LgAiBmO6uPy3JB7ydmXXhorZV55RP.xQTltElplVGiOVcR?startTime=1651395685000 Title: Label-free Domain Adaptation and Multimodal Manifold Learning with Riemannian Geometry Abstract: Recently, Riemannian geometry has become a central ingredient in a broad range of data analysis and learning tools. Broadly, it facilitates features of complex high-dimensional data with a known non-Euclidean geometry. In this ... Read more

הכנס הראשון למחקר מבוסס-נתונים של האינטרנט בישראל

Faculty of Law Building 306, room 200 Faculty of Law Building 306, room 200

Videos from the conference are available here:  https://www.isoc.org.il/event/conference-data-based-internet-research-in-israel When: 10/5/2022, 9-13 What: https://dsi.biu.ac.il/internet-event-2022-agenda Where: Law Building 306 Room 200, Bar-Ilan University    

AI Data Science Summit 2022

Auditorium of the College of Management 2 Elie Wiesel Street Rishon LeTsiyon, Center District 7579806

Prof. Gal Chechik, Director of AI at NVIDIA, Professor at BIU Title: Personalizing Federated learning with hypernetworks Abstract: Federated learning (FL) is the task of learning a model over multiple disjoint local datasets. It is particularly useful when local data cannot be shared due to privacy, storage, or communication constraints. Personalized Federated Learning (PFL) allows each ... Read more

Mechanism Design with Moral Bidders. Dr. Sigal Oren (BGU).

Building 216 room 201

Next week's colloquium will be given by Dr, Sigal Oren from Ben Gurion University. The lecture will be given in Person. Title:  Mechanism Design with Moral Bidders Abstract: A rapidly growing literature on lying in behavioral economics and psychology shows that individuals often do not lie even when lying maximizes their utility. In this work, we attempt to incorporate these findings into ... Read more

Better Environments for Better AI. Sarah Keren (Technion)

Building 216 room 201

Title:  Better Environments for Better AI  Abstract: Most AI research focuses exclusively on the AI agent itself, i.e., given some input, what are the improvements to the agent’s reasoning that will yield the best possible output? In my research, I take a novel approach to increasing the capabilities of AI agents via the use of ... Read more

Law and Data Science Collaboration workshop

Faculty of Law Building 306, room 200 Faculty of Law Building 306, room 200, Israel

See details in following pdf file:   שיתוף פעולה מחקרי בין מדע הנתונים ומשפטים C

(R?)evolution Times. Prof. Moshe Tennenholtz (Technion)

Building 216 room 201

Prof. Moshe Tennenholtz, Technion Will lecture on: (R?)evolution Times Recent years have shown dramatic progress in AI. Deep learning approaches employing the so-called "foundational models" are shaking the grounds of technology allowing for innovative products and services at quite an amazing speed. Criticisms and failures of these approaches have been considered: the need to incorporate ... Read more

Party Tricks: On Primaries and Gerrymandering. Omer Lev (BGU)

CS colloquium lecture by Dr. Omer Lev from Ben-Gurion University. Title: Party Tricks: On Primaries and Gerrymandering Abstract: In the last few years, the effects that primaries and gerrymandering have on election outcomes became a commonly debated issue, particularly in the US. Both primaries (candidate selection by parties) and district-based elections are examples of mechanisms that involve adding stages to a decison-making ... Read more

Mahmood Sharif Guest Lecture From TAU – Learning Club 12.6.22

###### Meeting Info ###### Title: Toward robust malware detection and faithfully evaluating the robustness of neural networks Abstract: Adversarial examples have emerged as a profound challenge and a critical concern for several application domains, sparking interest in developing adversarially robust machine-learning (ML) models and reliable methods for assessing robustness. In this talk, I will discuss ... Read more

Ofir Lindenbaum Guest Lecture From BIU – Learning Club 19.6.22

The recording of Ofir's talk and slides is available here. ###### Meeting Info ###### Title: Deep learning for tabular biomedical data Abstract: Biomedical datasets are often low-sample-size or high-dimensional. Practitioners in this domain prefer linear or tree-based models over neural networks since the latter are harder to interpret and tend to overfit when applied to tabular ... Read more

Generalization in Deep Learning Through the Lens of Implicit Rank Minimization. Nadav Cohen (TAU).

Building 216 room 201

CS colloquium lecture will be given by Dr. Nadav Cohen from Tel-Aviv University. Title: Generalization in Deep Learning Through the Lens of Implicit Rank Minimization Abstract: Understanding deep learning calls for addressing three fundamental questions: expressiveness, optimization and generalization.  Expressiveness refers to the ability of compactly sized neural networks to represent functions capable of solving real-world ... Read more

TAU Style: inversion, editing, and applications of StyleGAN. Dr. Amit Bermano from Tel-Aviv University (CS Colloquium)

Building 216 room 201

(CS Colloquium) TAU Style: inversion, editing, and applications of StyleGAN. Dr. Amit Bermano Tel-Aviv University  Abstract:  The generative abilities of GANs are revolutionizing the field of image synthesis and manipulation. Specifically, StyleGAN reaches the highest levels of image quality, and has become the de-facto golden standard for the editing of facial images. StyleGAN is unsupervised, ... Read more

Recovering Data Semantics. Dr. Roee Shraga (CS Colloquium)

Building 203 Room 221

Sunday, December 4, 2022 11:00 A.M. Building 203 Room 221 Dr. Roee Shraga Northeastern University in Boston י רצ ה על Will lecture on Recovering Data Semantics In data science, it is increasingly the case that the main challenge is finding, curating, and understanding the data that is available to solve a problem at hand. ... Read more

Genomic language model for function prediction of microbial genes – Danielle Miller (TAU)

בחדר 212 בניין 212

דוקטורנטית מאת״א תבוא להרצות על מודלי שפה לגנומים בקטריאלים. מוזמנים להגיע ולהפיץ לסטודנטים ולחברי סגל נוספים. ההרצאה תתקיים בשעה 14:00 ביום ב׳ 12.12 בחדר 212 בניין 212. כמו כן, אני מתכנן לשדר אותה בזום: https://us02web.zoom.us/j/5509052372 Title:  Genomic language model for function prediction of microbial genes Abstract: Revealing the function of uncharacterized genes is a fundamental challenge in an era of ever-increasing ... Read more

The tree reconstruction game: phylogenetic reconstruction using reinforcement learning. Dana Azouri (TAU)

Building 212 Room 212

The tree reconstruction game: phylogenetic reconstruction using reinforcement learning Dana Azouri דוברת: דנה עזורי, דוקטורנטית מאת״א. תתקיים בחדר 212 בניין 212. הרצאה בנושא שחזור עצים פילוגנטיים באמצעות למידת חיזוקים - יום ב׳ 26.12 בשעה 14:00 The following two fields have never interacted before: reinforcement learning and molecular evolution. Here we develop a reinforcement-learning algorithm to ... Read more

בינה מלאכותית במרחב האקדמי

אולם קונצרטים בניין מוזיקה (1005)

חבר/ת סגל שלום, הפקולטה למדעי הרוח באוניברסיטת בר-אילן מזמינה אותך לכנס "בינה מלאכותית במרחב האקדמי" מה ההבדל בין בינה מלאכותית לתבונה אנושית? האם צ׳אט בוט יכול להחליף אותנו במשימות האקדמיות, לכתוב עבודות, לחבר מסמכים במקומנו? מהן הסכנות והיתרונות של הChatGPT מבחינה אקדמית ואיך זה ישפיע על החינוך בעתיד הלא רחוק?  12/3-13/3 בשעה 9:30-13:30 אולם קונצרטים ... Read more

Advanced Machine Learning Methods to Accelerate Materials Discovery  (Santiago Miret, Intel)

Building 605, room 11

Hi everyone, You are invited to attend the talk of Santiago Miret at the NLP group seminar that will be held on Thursday 9.3.23, at 11 am. The talk will last approximately 1.5 hours including Q&A. See more details below. Best Regards, Idan Location: Building 605, room 11 Title: Advanced Machine Learning Methods to Accelerate Materials ... Read more

DSI Dinner – March 13, 2023

The Gonda Multidisciplinary Brain Research Center (building 901), Bar-Ilan University

CLICK HERE FOR PHOTOS FROM THE EVENT The event took place at BIU’s Brain Research Center hall (Building 901). Agenda:  17:00-17:15: Gathering and refreshments  17:15-17:30: Opening notes Prof. Onn Shehory 17:30-17:40: Prof. Maayan Zhitomirsky-Geffet, Sarit Sambol-Szasz (Libraries and Information System) Digital Humanities Tools and Resources (part1, part2) 17:40-18:30: Selected talks by DSI grant recipients:   Dr. ... Read more

BIU learning club – Dan Rosenbaum – Functa: data as neural fields

Location:Engineering building (1103), room 329Title:Functa: data as neural fieldsAbstract:It is common practice in deep learning to represent a measurement of the world on a discrete grid, e.g. a 2D grid of pixels. However, the underlying signal represented by these measurements is often continuous, e.g. the scene depicted in an image. A powerful continuous alternative is ... Read more

BIU learning club – Students’ talks

On Sunday 26.03.23, at 12:00 PM, we will have our third session of students’ presentations. In this session, four students from BIU will present their work. Note that, unlike regular learning club meetings, this meeting will last 2 hours, and will include lunch. It will take place at the Engineering building (1103) in room 329. ... Read more

BIU learning club – Alon Cohen – Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function Approximation

Title:Efficient Rate Optimal Regret for Adversarial Contextual MDPs Using Online Function ApproximationAbstract:We study learning tabular finite-horizon Markov Decision Processes with adversarially-chosen contexts. Following latest literature, we assume a realizable function class that maps between context and MDP as well as access to online regression oracles that fits the best function given prior observations. This setting ... Read more

BIU learning club – Yuval Pinter – When Language Models Meet Words

Location:Engineering building (1103), room 329Title:When Language Models Meet WordsAbstract:Over the last few years, deep neural models have taken over the field of natural language processing (NLP), brandishing great improvements on many of its sequence-level tasks. But the end-to-end nature of these models makes it hard to figure out whether the way they represent individual words ... Read more

BIU learning club – Assaf Arbelle – What is next in Vision and Language models?

Location:Building 1300 (students’ dorms), room 1Title:What is next in Vision and Language models?Abstract:In recent years, two mostly separated fields of machine learning, computer vision and natural language processing, have gradually become closer. Advancements in each field have greatly influenced the other, driven in part by the abundance of weekly annotated data in the form of ... Read more

Getting More from Your GPU – Tutorial by Yuval Mazor

604/62

NOTE: Link to slides in presentation - Getting More from Your GPU Due to a technical problem there is no recording of this, however, here is a link to a youtube video by Yuval on A Practical Guide for Reducing DNN Training Time -------------------------------------------------------------------------------------------------- This is a computing Tutorial hosted and organized by the DSI ... Read more

BIU learning club – Amichai Painsky – Inferring the Unseen

Location:Engineering building (1103), room 329Title:Inferring the UnseenAbstract:Consider a finite sample from an unknown distribution over a countable alphabet. Unobserved events are alphabet symbols which do not appear in the sample. Estimating the probabilities of unobserved events is a basic problem in statistics and related fields, which was extensively studied in the context of point estimation. ... Read more

BIU learning club – Kfir Levy – Beyond SGD: Efficient Learning with Non i.i.d. Data

Location:Engineering building (1103), room 329Title:Beyond SGD: Efficient Learning with Non i.i.d. DataAbstract:The tremendous success of the Machine Learning paradigm heavily relies on the development of powerful optimization methods. The canonical algorithm for training learning models is SGD (Stochastic Gradient Descent), yet this method has several limitations. In particular, it relies on the assumption that data-points ... Read more

BIU learning club – Moshe Eliasof – Improving Graph Neural Networks with Learnable Propagation Operators

Location:Engineering building (1103), room 329Title:Improving Graph Neural Networks with Learnable Propagation OperatorsAbstract:Graph Neural Networks (GNNs) are limited in their propagation operators. In many cases, these operators often contain non-negative elements only and are shared across channels, limiting the expressiveness of GNNs. Moreover, some GNNs suffer from over-smoothing, limiting their depth. On the other hand, Convolutional ... Read more

BIU learning club – Shalev Shaer – Betting as a mechanism to make reliable discoveries

Zoom link: https://biu-ac-il.zoom.us/j/4685913265 Title:Betting as a mechanism to make reliable discoveries Abstract:This talk introduces a new statistical testing framework that allows researchers to analyze an incoming i.i.d. data stream with any arbitrary dependency structure, and safely conclude whether a feature is conditionally associated with the response under study. We allow the processing of data points online, as soon ... Read more

Featured Featured

DSI Retreat: June 14-15, 2023

C Hotel Neve Ilan C Hotel, Neve Ilan, Israel

Photos from the Event DSI RETREAT 2023   This year's retreat will take place June 14-15 in C-HOTEL NEVE ILAN and is open for all DSI members and their graduate students. We would like to remind you that: The DSI retreat will take place 14-15.6.2023 - we hope to circulate agenda highlights and a draft schedule soon. This ... Read more

BIU NLP & Network Spotlight EVENT

Wohl Convention Center, Bar-Ilan University Anna & Max Webb St. Ramat-Gan.

Welcome to the Bar-Ilan Interdisciplinary Conference on Natural Language Processing (NLP) and Networks! We cordially invite researchers from academia and industry to join us for this unique and intellectually stimulating event, where we bring together two prominent areas of research: NLP and Networks. This conference has been thoughtfully designed to cater to experts and enthusiasts ... Read more

Bioinformatics Day

Auditorium C50, Nanotechnology Building (bldg. 206), Bar-Ilan University

https://dsi.biu.ac.il/wp-content/uploads/2023/09/bio-event-13-september.pdf