BIU AI and ML Learning Club – June 9, Testing for Dependency of Databases

CS Bldg 503, Seminar Room 226

On June 9,  Dr. Wasim Huleihel from the Tel Aviv university will give a talk titled: Testing for Dependency of Databases Abstract: In this talk, we investigate the problem of detecting the dependency between two random databases represented as matrices. This is formalized as a hypothesis testing problem, where under the null hypothesis, the two ... Read more

BIU AI and ML Learning Club – June 16, Revealing Latent Hierarchical Structures in High-Dimensional Data Using Hyperbolic Representations

חדר ישיבות 329, הנדסה

On June 16,  Dr. Ronen Talmon from the Technion will give a talk titled: Revealing Latent Hierarchical Structures in High-Dimensional Data Using Hyperbolic Representations Abstract: The tremendous success of the Machine Learning paradigm heavily relies on the development of powerful optimization methods, and the canonical algorithm for training learning models is SGD (Stochastic Gradient Descent). ... Read more

BIU AI and ML Learning Club, June 23 – BIU Students research talks

CS Bldg 503, Seminar Room 226

On June 23,  we will have 4 BIU Students giving the following talks on their research progress. First hour (12:00-13:00) will be dedicated for the students talks Second hour (13:00 - 14:00) for networking. 12:00 - 12:15 Presenter: Osnat Drien Lab Head: Prof. Yael Amsterdamer Title: Query-Guided Resolution in Uncertain Databases Abstract: We present a ... Read more

BIU AI and ML Learning Club, June 30 – What Makes Data Suitable for Deep Learning?

CS Bldg 503, Seminar Room 226

On June 30,  Dr. Nadav Cohen from the Tel Aviv University will give a talk titled: What Makes Data Suitable for Deep Learning? Abstract: Deep learning is delivering unprecedented performance when applied to various data modalities, yet there are data distributions over which it utterly fails. The question of what makes a data distribution suitable ... Read more

BIU AI and ML Learning Club, July 7 – Local Glivenko-Cantelli (or: estimating the mean in infinite dimensions)

חדר ישיבות 329, הנדסה

On July 7,  Prof. Aryeh Kontorovich from the Tel Aviv University will give a talk titled: Local Glivenko-Cantelli (or: estimating the mean in infinite dimensions) Abstract: If μ is a distribution over the d-dimensional Boolean cube {0,1}ᵈ, our goal is to estimate its mean p∈ᵈ based on n iid draws from μ. Specifically, we consider ... Read more

DSAI Dinner 2024, July 10, 2024

Nano Building (206), Auditorium room 051

  The Bar-Ilan Data Science and AI institute (BIU DSAI) is glad to invite you to its annual dinner event. The event is open to all BIU researchers interested in data science and AI including faculty, postdoctoral fellows and graduate students.   This will be an opportunity for us all to meet, learn about recent ... Read more

BIU AI and ML Learning Club, July 7 – Protecting AI From Theft with 2-Party Security

חדר ישיבות 329, הנדסה

On July 14,  Dr. Adam Hakim from Microsoft WSSI will give a talk titled: Protecting AI From Theft with 2-Party Security Abstract: Large language models (LLMs) have recently seen widespread adoption, in both academia and industry. As these models grow, they become valuable intellectual property (IP), reflecting enormous investments by their owners. Moreover, the high ... Read more

BIU Learning Club, November 18 – Exploiting Symmetries for Learning in Deep Weight Spaces

חדר ישיבות 329, הנדסה

On November 18,  Dr. Haggai Maron from the Technion will give a talk titled: Exploiting Symmetries for Learning in Deep Weight Spaces Abstract: This talk explores the emerging research direction that studies neural network weights as a novel data modality. We'll discuss recent advances in processing and analyzing raw weight matrices, which exhibit inherent symmetries ... Read more

BIU Learning Club, November 25 – Statistical curriculum learning — An elimination algorithm achieving the weak oracle risk

חדר ישיבות 329, הנדסה

On November 25,  Dr. Nir Weinberger from the Technion will give a talk titled: Statistical curriculum learning -- An elimination algorithm achieving the weak oracle risk Abstract: Curriculum Learning (CL) is a successful machine learning strategy that improves a learner’s performance by ordering the tasks according to difficulty, similarly to the way humans learn.  However, ... Read more

סמינר: בינה מלאכותית יוצרת, מתודולוגיות חדשות במחקר והוראה במדעי האדם

אולם קונצרטים בניין מוזיקה (1005)

המכון בשיתוף עם הפקולטה למדעי הרוח מזמינים אותכם לכנס בנושא בינה מלאכותית יוצרת, מתודולוגויות חדשות במחקר והוראה במדעי האדם. הסמינר מיועד לכלל האוניברסטאות, לחברי סגל וסטודנטים לתארים מתקדמים.  להרשמה, פיתחו את הקובץ מתחת לפוסטר, וליחצו על הלינק להרשמה. נשמח לראותכם BIURuachAIAd20246