Informed Data Science – CS Colloquium talk by Dr. Amir Gilad Duke University (Duke)

Building 403 Room 67

Monday, 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

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

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

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

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

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

(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

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

Prof. Gal Chechik Bar-Ilan University: Learning with visual foundation models for Gen AI

CS Auditorium (Bldg. 503)

On May 23,  Prof. Gal Chechik Bar-Ilan University will give a lecture on: Learning with visual foundation models for Gen AI Abstract: Between training and inference, lies a growing class of AI problems that involve fast optimization of a pre-trained model for a specific inference task. These are not pure “feed-forward” inference problems applied to ... Read more