Calendar of Events
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Law and Data Science Collaboration workshop
Law and Data Science Collaboration workshop
See details in following pdf file: שיתוף פעולה מחקרי בין מדע הנתונים ומשפטים C
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(R?)evolution Times. Prof. Moshe Tennenholtz (Technion)
(R?)evolution Times. Prof. Moshe Tennenholtz (Technion)
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
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Party Tricks: On Primaries and Gerrymandering. Omer Lev (BGU)
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
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Mahmood Sharif Guest Lecture From TAU – Learning Club 12.6.22
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
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Ofir Lindenbaum Guest Lecture From BIU – Learning Club 19.6.22
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
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Investigating fine-tuning of pre-trained language models. Marius Mosbach, from Saarland University
Investigating fine-tuning of pre-trained language models. Marius Mosbach, from Saarland University
On the 21st of June Marius Mosbach, from Saarland University will give a talk at the lab. He's here for a visit of about 2.5 weeks (starting from June 7th), so be nice to him and say hi =) If you'd like to chat with him (and you should!), add your name in the attached ... Read more
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Generalization in Deep Learning Through the Lens of Implicit Rank Minimization. Nadav Cohen (TAU).
Generalization in Deep Learning Through the Lens of Implicit Rank Minimization. Nadav Cohen (TAU).
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