Dec. 30th 2018, Sun. 12:00 , Roy Bar-Haim (webpage). Debating Technologies group, IBM Research AI - Haifa. Location: Gonda Building (901), Room 101.

Registration: MaorT@most.gov.il (Name, Institution, department, position email and mobile number requested). ----- In all domains of human activity, we are more and more faced with the problem of understanding and extracting knowledge from standard, big and complex data, often multi-sources (with mixture of numerical, textual, image, social networks data).   Data Science, considered as a science ... Read more

הרצאה בנושא  Big Data and the Right to Political Participation שנכתב ע"י ד"ר מיכל סליטרניק, סמינר המחלקתי של הפקולטה למשפטים: יום ג' 12.3.19 בין השעות 14:00-15:30 בחדר סגל, בניין 306.

Mar. 31st 2019, Sun. 12:00 , Sivan Sabato (webpage). Ben-Gurion University.   Location: Nano Building (206), Room B991. A Universally Consistent 1-Nearest-Neighbor Algorithm   Abstract: We show a 1-Nearest-Neighbor algorithm that is universally strongly-Bayes-consistent in all metric spaces where such a learner exists. This is the first learning algorithm known to enjoy this property. Joint ... Read more

Apr. 7th 2019, Sun. 12:00 , Aviv Tamar (webpage). Technion - Israel Institute of Technology. Location: Nano Building (206), Room B991. Learning Representations for Planning Abstract: How can we build autonomous robots that operate in unstructured and dynamic environments such as homes or hospitals? This problem has been investigated under several disciplines, including planning (motion ... Read more

May. 12th 2019, Sun. 12:00 , Lihi Zelnik-Manor and Asaf Noy (webpage). Technion - Israel Institute of Technology and Alibaba. Location: Nano Building (206), Room B991. AutoML by Alibaba: Architecture Search, Anneal and Prune Abstract: Manual network architecture search and hyper-parameter tuning of neural network based algorithms could be a very interesting task but also ... Read more

June. 2nd 2019, Sun. 12:00 , Oren Freifeld (webpage). Ben-Gurion University. Location: Nano Building (206), Room B991. Geometric transformations in deep learning and Bayesian nonparamteric mixture models. Abstract: This talk will focus on two of the main research directions at our Vision, Inference, and Learning group: 1) Geometric transformations in deep learning and 2) Bayesian ... Read more

Yuval from NVIDIA will be giving a tutorial on containers, docker containers, NGC containers, how to use them, etc. - relvant to both novice users and advanced users.

For details and registration: https://sites.google.com/datalab.cs.biu.ac.il/biusummerschool/home?authuser=4

For details and registration: https://sites.google.com/datalab.cs.biu.ac.il/biusummerschool/home?authuser=4

Title: Polynomial-time algorithms are not always welcome – sparse PCA as a case study When: October 27, Sunday, 12:00 Where: Gonda building, room 101 Abstract: The taxing computational effort that is involved in solving some high-dimensional statistical problems, in particular problems involving non-convex optimization, has popularized the development and analysis of  algorithms that run efficiently (polynomial-time) but ... Read more

במסגרת שיתוף הפעולה בין מחב"א לחברת AWS, אני שמח להזמין אתכם ליום עיון בנושא שירותי מחקר בענן. האירוע מיועד לחוקרים, מרצים ועוזרי מחקר המבצעים כיום פעילות מחקר בענן או שוקלים לבצע מחקר בעתיד באמצעות שירותי ענן. מטרת האירוע לתת לחוקרים את הכלים להתמקד במחקר בצורה יעילה. האירוע יתקיים ב-17.11.2019 באוניברסיטה בר-אילן, הפקולטה למדעי החיים, בנין 212, קומה 2, ... Read more

Title: Heuristic learning on the border between success and failure Abstract: Many popular hypothesis classes, such as neural-networks or decision trees, are computationally hard to learn. In practice, however, heuristic algorithms are used to learn these classes with remarkable success. To better understand this gap, we explore probabilistic models where a small change in the ... Read more

Nadav Cohen from TAU Location: Gonda building (901), room 102. Time: Sunday Nov 24th, 12:00 AM -- 13:00 AM. Title: Analyzing Optimization and Generalization in Deep Learning via Trajectories of Gradient Descent Abstract: Understanding deep learning calls for addressing the questions of: (i) optimization --- the effectiveness of simple gradient-based algorithms in solving neural network ... Read more

Special seminar on urban networks by Prof. Gourab Ghoshal from University of Rochester, NY: Gourab will be around from Nov. 25 - 28. If you are interested in meeting with him, please let me know. Please feel free to forward to all relevant groups, peers. PosterGhoshal  

Title: Second-order Optimization Made Practical Abstract: Optimization in machine learning, both theoretical and applied, is presently dominated by first-order gradient methods such as stochastic gradient descent.  Higher-order (preconditioned) optimization methods have become far less prevalent, despite compelling theoretical properties, due to their impractical computation, memory and communication costs.  I will present some recent theoretical, algorithmic ... Read more

Open for all biu students interested to learn how to best utilize the available GPU hardware. Wednesday, December 4⋅10:00am – 12:00pm חדר ישיבות 329, הנדסה Please download following materials before session: profilingTutorial Add to calendar: https://calendar.google.com/event?action=TEMPLATE&tmeid=NGNjb2s0azl0OG9qMmdpZjl2Z3Q5cmZzOWQgb3Jlbi5nbGlja21hbkBt&tmsrc=oren.glickman%40gmail.com Post Event Materials: Talk:  https://www.youtube.com/watch?v=m5He_FlhcRo&feature=youtu.be&t=1 Deck:  https://raanan.blob.core.windows.net/biu/A%20Practical%20Guide%20for%20Reducing%20DNN%20Training%20Time%E2%80%8B.pptx?sp=r&st=2019-12-08T12:50:55Z&se=2020-03-18T20:50:55Z&spr=https&sv=2019-02-02&sr=b&sig=6YtI4y5mhfDK3A9zvpuTd3vLMpyNgITRyouHbz9Hhgs%3D Blog Post: https://sagivtech.com/2017/09/19/optimizing-pytorch-training-code/

Title: GANs for Real-Life Video Applications. Abstract: This talk will focus on two research papers that demonstrate the use of generative adversarial networks for real-life video applications, through face and full-body synthesis. The first paper (“Live Face De-Identification in Video”), proposes a novel method for face de-identification, that enables fully automatic video modification at high ... Read more

Speaker: ALON GONEN Date : 19/12/2019 - 12:00 Title : Beyond Worst Case In Machine Learning: The Oracle Model Abstract: In recent years there has been an increasing gap between the success of machine learning algorithms and our ability to explain their success theoretically. Namely, many of the problems that are solved to a satisfactory degree of precision ... Read more

Sanjeev Khudanpur from John-Hopkins University Two Ideas for Improving Automatic Speech Recognition: One Elegant, and One Very Useful! The Kaldi tools for automatic speech recognition (ASR) are being widely used both for research and for large-scale deployments.  Many innovations large and small have gone into keeping Kaldi up-to-date in this fact-moving field.  I will describe how two ... Read more

Sunday (19.1.20 12:00) we will host Idan Szpektor from Google. The talk will take place at Gonda (building 901) room 101. Title: Dynamic Composition in Conversational Domain Exploration In this talk I will introduce conversational domain exploration, where the user’s goal is to enrich her knowledge of a given domain by conversing with an informative bot.  Such ... Read more

Shauli Ravfogel Title: Unsupervised Distillation of Syntactic Information From Contextualized Neural Representation. Abstract: Contextualized word representations, such as ELMo and BERT, were shown to perform well on a various of semantic and structural (syntactic) task. In this work, we tackle the task of unsupervised disentanglement between semantics and structure in neural language representations: we aim to ... Read more

Part of The Israel Statistical Association workshop: Explainable AI (XAI) workshop Title: Explaining visual understanding: Learn to reason about the perceived world. Speaker: Prof. Gal Chechik Abstract: AI aims to build systems that can interact with their environment, with people and with other agents in the real world. This vision poses hard algorithmic challenges for ... Read more

Talk at AI For Human Languages (free student tickets available for biu students - talk to Reut) Title: What's wrong with Hebrew NLP? And How to Make it Right Speaker: Prof. Reut Tsarfaty The ability to automatically process massive volumes of unstructured texts and turn them into structured information is key to many success stories ... Read more

Title: Differentially Private Ordinary Least Squares Abstract: Linear regression is one of the most prevalent techniques in machine learning; however, it is also common to use linear regression for its explanatory capabilities rather than label prediction. Ordinary Least Squares (OLS) is often used in statistics to establish a correlation between an attribute (e.g. gender) and ... Read more