Containers101: IBM cloud computing technical workshop series
Containers101: Containers, Docker, Kubernetes When: Tue 26/1/2020 14:00-16:00 (Zoom). Details: http://dsi.biu.ac.il/student-position-for-research-project-on-bots-in-social-networks/ Registration: https://forms.gle/aNBiqc1dG1XshLp3A
Digital Governance in the Times of Covid-19
בשבוע הבא, ב-17-18 בפברואר יתקיים כנס בינלאומי בנושא Digital Governance in the Times of Covid-19. מצ"ב תוכנית הכנס. נשמח שתצטרפו אלינו. שימו לב שיש להירשם מראש כאן. בנוסף, רבים מכם וודאי יתעניינו בספר חדש שזמין כעת באופן מקוון דרך הספריה: Legal Informatics (D. M. Katz et al. ed., Cambridge University Press) (2021) ניתן לגשת לספר ... Read more
Reasoning about Perception (talk by Prof. Gal Chechik, AI Week)
New methods to understand and generate visual scenes with novel combinations and complex interactions. https://aiweekonline.b2b-wizard.com/expo/agenda
NVIDIA GPU Programming workshop
When: 9/3/2020 10:00-12:00 Agenda: 10-10:30: Liron Friend, Developer Relations; Brief intro to Nvidia Nvidia’s Ambassador program for researchers Nvidia NGC: Nvidia docker containers, pretrained models and SDK’s 10:30 – 11:15: Gal Malca, Solution Architect Training neural networks with multi GPU training AMP – training with mixed precision Nvidia SMI and NSight with performance demo NGC ... Read more
Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization – Learning Club talk by Tamir Hazan
Title: Learning Randomly Perturbed Structured Predictors for Direct Loss Minimization Abstract: Direct loss minimization is a popular approach for learning predictors over structured label spaces. This approach is computationally appealing as it replaces integration with optimization and allows to propagate gradients in a deep net using loss-perturbed prediction. Recently, this technique was extended to generative ... Read more
BIU Learning Club 4.4.2021 — Ronen Basri — On the Connection between Deep Neural Networks and Kernel Methods
The recording of Ronen's talk: https://us02web.zoom.us/rec/share/lFyTCaXdH469BOuce3TgfdZQZ1pJlsy-Ei165FQPuiue6nGPHjpLgbOCF1hdvWEu.iDjrEpLTDMdUpiXJ Thanks to Ronen for the presentation and everyone who attended, Hey everyone, After the holiday, on Sunday 4.4.2021 at 12:00, we will host Ronen Basri from Weizman Institute. Ronen will present his work on the connection between deep neural networks and kernel methods. Zoom: https://us02web.zoom.us/j/88008797212pwd=TkFnME5OM3VqV2FjSlRGRTNLSVB1QT09 Meeting ID: 880 0879 7212 Passcode: ... Read more
Learning Club talk by Roni Livni
Time: Sunday Apr 11th, 2021 12:00 PM — 13:00 PM. The recording of Roi's talk: https://us02web.zoom.us/rec/play/7uL_4UkcH6PhgKWsSEn_lc3QOLqEuQOu7ax08fgnj93YgVhkfMM9_9f_2VbfaoqJFif7tpFffh4V6mt-.-MC-XWpEjtb97tvZ?continueMode=true On Sunday 11.4.2021 at 12:00, we will host Roi Livni from Tel-Aviv University. Roi will present his work on: "Regularization, what is it good for?". Zoom: https://us02web.zoom.us/j/83325342820?pwd=cUcxR2lJMzloL0pwNHJUWG0wNTQvUT09 Meeting ID: 833 2534 2820 Passcode: 449581 Title: Regularization, what is it good ... Read more
Learning to Plan and Planning to Learn – Learning Club talk by Aviv Tamar
Learning Club BIU - Aviv Tamar Title: Learning to Plan and Planning to Learn Abstract: Two main paradigms for solving sequential decision making problems are planning - searching through possible future outcomes to achieve a goal, and reinforcement learning (RL) - learning reactive policies through trial and error. This talk focuses on algorithmic interfaces between ... Read more
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks – Learning Club talk by Asaf Noy
Learning Club - Asaf Noy Title: A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks Abstract: Deep neural networks' remarkable ability to correctly fit training data when optimized by gradient-based algorithms is yet to be fully understood. Recent theoretical results explain the convergence for ReLU networks that are wider than those used in practice by ... Read more
Learning Club talk by Raja Giryes
on Sunday 2.5.2021at 12:00, we will host Raja Giryes from Tel-Aviv University. Title: Robustifying neural networks Abstract: In this talk I will survey several techniques to make neural networks more robust. While neural networks achieve groundbreaking results in many applications, they depend strongly on the availability of good training data and the assumption that the data ... Read more
BIU Learning Club 9.5.2021 — Brain Chmiel — NEURAL GRADIENTS ARE NEAR-LOGNORMAL: IMPROVED QUANTIZED AND SPARSE TRAINING
The recording of Brian's talk is available here: https://us02web.zoom.us/rec/play/q1MhnoNJqMOBCBpADGABiGx7BUErjRyRe61hIsrWZeVwn5h0Jewn9JtO2z5BzYtFUrMB7dKckS2Us0RK.tsVtRh_-0qN13UJI Zoom: https://us02web.zoom.us/j/84467714967?pwd=MW5pR216eUlvMXRFK0g2WHpNbjBVQT09 Meeting ID: 844 6771 4967 Passcode: 149008 Title: NEURAL GRADIENTS ARE NEAR-LOGNORMAL: IMPROVED QUANTIZED AND SPARSE TRAINING Abstract: While training can mostly be accelerated by reducing the time needed to propagate neural gradients (loss gradients with respect to the intermediate neural layer outputs) back ... Read more
Learning Club BIU talk by Yonathan Efroni
BIU Learning Club 23.5.2021 -- Yonathan Efroni -- Confidence-Budget Matching for Sequential Budgeted Learning Yonathan Efroni from Microsoft research Israel/New York. Zoom: https://us02web.zoom.us/j/84891223876?pwd=UGcyZU8rZHY2NGpTMFNuUFIzajVRUT09 Meeting ID: 848 9122 3876 Passcode: 750812 Title: Confidence-Budget Matching for Sequential Budgeted Learning Abstract: A core element in decision-making under uncertainty is the feedback on the quality of the performed actions. ... Read more
Learning Club talk by Yedid Hoshen
Hey, The recording of today's talk: https://us02web.zoom.us/rec/share/rR45YFjmksHuzP9SG__a-7_MmLdVI6Bq6OU9r4RIID2QbxCzPhcso_d_H-OFdcXT.v-J1Wj5nzanD8Ph5?startTime=1622365463000 Thanks to Yedid for presenting and everyone who attended, ----------------------------------- Hey everyone, On Sunday 30.5.2021 we will host Yedid Hoshen from the Hebrew University. Please see the details below. See you then, Roni ------ Zoom: https://us02web.zoom.us/j/84758320608?pwd=SWljZGxhT1lkK1c2U0YyaVVEclZFUT09 Meeting ID: 847 5832 0608 Passcode: 942440 Title: Scaling-up Disentanglement Abstract: Disentangling ... Read more
Speech Language and Deep Learning.
הרצאת חשיפה למחקר של פרופ' יוסי קשת בנושא של עיבוד קול ולמידת מכונה. https://us02web.zoom.us/j/86317829185 Joseph (Yossi) Keshet Department of Computer Science
Learning Club talk by Yair Carmon
Learning Club - Yair Carmon The recording of Yair's talk: https://us02web.zoom.us/rec/share/4qoVA4woNo0sguj1vvlUYtWZIYOpyuiKfNPxt2YY8wSv0QfV61sua-tbf6Z6AXXU.kLtZGmkcoTBn5uty?startTime=1622970316000 Zoom: https://us02web.zoom.us/j/84847086771?pwd=K2QrMnZrQ21XU2JaUi9KS24wUHN2QT09 Meeting ID: 848 4708 6771 Passcode: 607548 Title: Accuracy on the line: on the predictability of out-of-distribution generalization Abstract: To make machine learning reliable, we must understand generalization to out-of-distribution environments (unseen during training) in addition to the in-distribution generalization measured by ... Read more
Learning Club talk by Roi Reichart
The recording of Roi's talk: https://us02web.zoom.us/rec/share/TED6jHbAUWqMRm7ERD3Tft7-EdMta6RwWdUaGYYYnoTrE7vcxIMeC1EmkU1v_LFp.xfF0lKSytaBECNuL?startTime=1623574979000 Learning Club - Roi Reichart On Sunday 13.6.2021 at 12:00, we will host Roi Reichart from the Technion. Zoom: https://us02web.zoom.us/j/83866349257?pwd=Y1g2R3U1akNLQ1MrNXh5QUcxME8ydz09 Meeting ID: 838 6634 9257 Passcode: 754963 Title: CausaLM: Causal Model Explanation Through Counterfactual Language Models Abstract: Understanding predictions made by deep neural networks is notoriously difficult, but also crucial to ... Read more
Learning Club talk by Joanathan Berant
The recording of Jonathan's talk: https://us02web.zoom.us/rec/share/3n_NxS_A2xCc1fNRyToKsNIT70oCEDuirBM-UW0BB9eZPasSGsUL-3Cl9D4xbPYu.YjtwPGXF1--IJTkK?startTime=1624179875000 Thanks to Jonathan for presenting and everyone who attended, Learning Club - Joanathan Berant On Sunday 20.6.2021 at 12:00, we will host Jonathan Berant from Tel-Aviv university. ------ Zoom: https://us02web.zoom.us/j/87317183515?pwd=VHJyUUdVTG0rMlVMbzUyaGZNTHhzZz09 Meeting ID: 873 1718 3515 Passcode: 617148 Title: Beyond supervised learning: generalization, few-shot learning, and robustness Abstract: Pre-trained language models combined ... Read more
Workshop: State-of-the-Art Natural Language Processing (NLP) for Research in the Social Sciences and Humanities
For recording of workshop see: https://idsi.net.technion.ac.il/nlp-workshop ------------------------------------------------- Israel Data Science Initiative is pleased to sponsor a Workshop on: State-of-the-Art Natural Language Processing (NLP) for Research in the Social Sciences and Humanities Date: May 27, 2021 Session 1: 11:00 – 13:00 Models and Methods Lunch break Session 2: 14:00 – 15:30 Use Case with Python ... Read more
Learning Club BIU talk by Sagie Benaim
The recording of the talk: https://drive.google.com/file/d/1zxX8iQrwabXvjCo8RBbu4wolGMYdnf3e/view?usp=sharing ----- On Sunday 27.6.2021 at 12:00, we will host Sagie Benaim fromTel-Aviv university. Please see the details below. Zoom: https://us02web.zoom.us/j/88063900417?pwd=VWRDUy9ld0d1eVpocFhVOEcvd0FNUT09 Meeting ID: 880 6390 0417 Passcode: 683072 Title: Structure-Aware Manipulation of Images and Videos Abstract: Methods for image and video manipulation, such as texture and style transfer, are a subject of ... Read more
Activity as a novel medical diagnostic tool – Dr. Elad Yom-Tov from Microsoft Research.
חדר מחלקה – בניין 216 קומה 2 2nd Floor Colloquium, Building 216, Room 201CS Colloquium talk by Dr. Elad Yom-Tov from Microsoft Research. Title: Online activity as a novel medical diagnostic tool Abstract: The majority of internet users report that they use the web to find information about their medical concerns. Data generated during this search process provides detailed insights into users’ interests and activities at high temporal ... Read more
DSI Dinner – October 2021
Building 206 – Nanotechnology Complex; Room C-50YES - DSI Dinners are back!!! After over a year in which the BIU DS community did not gather face to face, this will be an opportunity for us all to meet, learn about recent research activities and enjoy a dinner event. We are excited to share with you the details of the TASHPAB Fall ... Read more
Diffusion Models Beat GANs? – Eliya Nachmani (TAU & FAIR)
Recording: https://us02web.zoom.us/rec/share/AJjsXIl29nyD0ZSbadWHFd54QJFAB8sfV0b1WdcSY-kMvJE68rmdk595OO_yCUoK.f4P_M3-T4nfR5h91 Eliya Nachmani from TAU & FAIR. Title: Diffusion Models Beat GANs? Abstract: I will give a short introduction to generative diffusion models and present their performance compared to other generative models (including GANs). Moreover, I will present two works that we did in the last year: (i) Noise Estimation for Generative Diffusion Models: ... Read more
Marginal Contribution Feature Importance – an Axiomatic Approach for Explaining Data. Amnon Catav (TAU).
The recording of Amnon's talk: https://us02web.zoom.us/rec/share/TxC7tgud-XyP-h577Pa-EwhLt9Bi4P7BCurUbafwRuW_-UiCxJDG8L9gAJylLiU4.OMMHDUVzuEc4ZVnE?startTime=1636279531000 Title: Marginal Contribution Feature Importance - an Axiomatic Approach for Explaining Data Abstract: In recent years, methods were proposed for assigning feature importance scores to measure the contribution of individual features. While in some cases the goal is to understand a specific model, in many cases the goal is ... Read more
A Textless Approach for Generative Spoken Language Modeling – Yossi Adi, from FAIR
On Sunday 21.11.2021 at 12:00, we will host Yossi Adi, from FAIR. Zoom: https://us02web.zoom.us/j/85941444168?pwd=S3pvNnVYTkx6RWsvSzFxTVVvdlFlZz09 Meeting ID: 859 4144 4168 Passcode: 584021 Title A Textless Approach for Generative Spoken Language Modeling Abstract An open question for AI research is creating systems that learn from natural interactions as infants learn their first language(s): spontaneously and without access ... Read more
BIU LawDataLab – opening
306/200BIU LawData - year opening event. For details see: ארוע פתיחת מעבדה א 23.11.2021
A Theoretical Analysis of Generalization in Graph Convolutional Neural Networks – Ron Levie from Ludwig Maximilian University of Munich
Recording: https://us02web.zoom.us/rec/share/fHCCma3ibcwJDDysXJeiVXwJgIrZB2y6KP70r0lSoVx6f66BFk00LyWd7af-fPpy.RD5WoGdSZW92a31V?startTime=1638093861000 --------------------------------------------------------------------- Hey Everyone, On Sunday 28.11.2021, we will host Ron Levie from Ludwig Maximilian University of Munich. Zoom: https://us02web.zoom.us/j/86540744550?pwd=bTlWMnZSWU1KcHFaSVlaUmR3aDNNUT09 Meeting ID: 865 4074 4550 Passcode: 748585 Title A Theoretical Analysis of Generalization in Graph Convolutional Neural Networks Abstract In recent years, the need to accommodate non-Euclidean structures in data science has brought a ... Read more
Equivariant Subgraph Aggregation Networks – Haggai Maron (NVIDIA Research)
The recording from Haggai's talk: https://us02web.zoom.us/rec/share/jCgJIjXL_UM5KV2z7NwgL3ij2SuLvrTLmVGF4OkI9Vk_J4RFfgYx79h9iC7Z41XQ.3FksbTtcNCIk-phG?startTime=1639303317000 On Sunday 12.12.2021, we will host Haggai Maron from NVIDIA Research. Zoom: https://us02web.zoom.us/j/85743049730?pwd=dVNRcVBJRlJxaTkrZzZkdSt1ajlUQT09 Meeting ID: 857 4304 9730 Passcode: 902259 Title: Equivariant Subgraph Aggregation Networks Abstract: Message-passing neural networks (MPNNs) are the leading architecture for deep learning on graph-structured data, in large part due to their simplicity and scalability. ... Read more
Generalization in RL – A Bayesian Perspective (Aviv Tamar, Technion)
On Sunday 19.12.2021, we will host Aviv Tamar from Technion. Zoom https://us02web.zoom.us/j/85352616833?pwd=ZDBQNVBESFg2cERlalRhbWNrbzIrQT09 Meeting ID: 853 5261 6833 Passcode: 897342 Title Generalization in RL - A Bayesian Perspective Abstract How can an agent learn to quickly perform well in an unknown task? This is the basic question in reinforcement learning (RL), and is critical for any ... Read more
The implicit bias of SGD: Minima stability analysis – Tomer Michaeli, Technion
The recording of the talk: https://us02web.zoom.us/rec/share/kIED6jkl9xH8y8pzyHAlYig11X11pbDjBqBsijV1kvrzIeOnElEr1ruFhTA1GVLN.vsmhBZvDEjvRx0Kc?startTime=1640513140000 Zoom https://us02web.zoom.us/j/83447514190pwd=cDVsc3Y0dWJOTFIwNlhSQmV5Vkpudz09 Meeting ID: 834 4751 4190 Passcode: 1212 Title The implicit bias of SGD: Minima stability analysis Abstract One of the puzzling phenomena in deep learning, is that neural networks tend to generalize well even when they are highly overparameterized. This stands in sharp contrast to classical wisdom, ... Read more
Learning with fewer labels in Computer Vision – Amir Bar – TAU
The recording of Amir's talk: https://us02web.zoom.us/rec/play/eErrSv8QOE9pC0bNNU4cB46ZiUXuKwbaEXv01MHvyFYTcwikE3Tb4FNob3A00Fi-6csubiImwmcE2OIl.sfukRxaffBiRikPo?startTime=1641117754000 Learning Club BIU - Amir Bar - TAU When Sun, January 2, 2022, 12pm – 1pm Zoom https://us02web.zoom.us/j/83447514190?pwd=cDVsc3Y0dWJOTFIwNlhSQmV5Vkpudz09 Meeting ID: 834 4751 4190 Passcode: 1212 Title: Learning with fewer labels in Computer Vision Abstract: In recent years, deep neural networks have transformed the field of Computer Vision. Current neural ... Read more
Informed Data Science – CS Colloquium talk by Dr. Amir Gilad Duke University (Duke)
Building 403 Room 67Monday, January 3, 2022 10:00 A.M. יום ב', א' בשבט תשפ"ב בשעה 10:00 Dr. Amir Gilad, Duke University Informed Data Science Data science has become prevalent in various fields that affect day-to-day lives, such as healthcare, banking, and the job market. The process of developing data science applications usually consists of several automatic systems that manipulate ... Read more
Perspectives on Privacy
See following pdf - פרספקטיביות 5.1.22 Link to Zoom - https://us02web.zoom.us/j/85399051733?pwd=UmJJSi9YR3A0a2JrTDlORytLbEQwQT09
Learning Club – Itai Lang – TAU – Geometric Adversarial Attacks and Defenses on 3D Point Clouds
Learning Club - Itai Lang - TAU - Geometric Adversarial Attacks and Defenses on 3D Point Clouds When: Sun, January 9, 2022, 12pm – 1pm Title: Geometric Adversarial Attacks and Defenses on 3D Point Clouds Abstract: Deep neural networks are prone to adversarial examples that maliciously alter the network's outcome. Due to the increasing popularity ... Read more
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
MLIS-TCE CONFERENCE – AI: From Hype to Productivity
Join us to the Annual Symposium of MLIS– the Technion AI center and TCE Center, on February 24, 2022, at ELMA Arts Complex . AI is now THE Buzz word, but what are the true current capabilities? What is state-of-the-art and what can be implemented? In this symposium, we differentiate fact from (current) fiction through ... Read more
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 201Dr. 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 201Dr. 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 201Prof. 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 UniversitySolving 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 201Speaker: 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 201Dr. 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 201Department 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 200Videos 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 7579806Prof. 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