Calendar of Events
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BIU learning club – Assaf Arbelle – What is next in Vision and Language models?
BIU learning club – Assaf Arbelle – What is next in Vision and Language models?
Location:Building 1300 (students’ dorms), room 1Title:What is next in Vision and Language models?Abstract:In recent years, two mostly separated fields of machine learning, computer vision and natural language processing, have gradually become closer. Advancements in each field have greatly influenced the other, driven in part by the abundance of weekly annotated data in the form of ... Read more
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Getting More from Your GPU – Tutorial by Yuval Mazor
Getting More from Your GPU – Tutorial by Yuval Mazor
NOTE: Link to slides in presentation - Getting More from Your GPU Due to a technical problem there is no recording of this, however, here is a link to a youtube video by Yuval on A Practical Guide for Reducing DNN Training Time -------------------------------------------------------------------------------------------------- This is a computing Tutorial hosted and organized by the DSI ... Read more
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BIU learning club – Amichai Painsky – Inferring the Unseen
BIU learning club – Amichai Painsky – Inferring the Unseen
Location:Engineering building (1103), room 329Title:Inferring the UnseenAbstract:Consider a finite sample from an unknown distribution over a countable alphabet. Unobserved events are alphabet symbols which do not appear in the sample. Estimating the probabilities of unobserved events is a basic problem in statistics and related fields, which was extensively studied in the context of point estimation. ... Read more
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BIU learning club – Kfir Levy – Beyond SGD: Efficient Learning with Non i.i.d. Data
BIU learning club – Kfir Levy – Beyond SGD: Efficient Learning with Non i.i.d. Data
Location:Engineering building (1103), room 329Title:Beyond SGD: Efficient Learning with Non i.i.d. DataAbstract:The tremendous success of the Machine Learning paradigm heavily relies on the development of powerful optimization methods. The canonical algorithm for training learning models is SGD (Stochastic Gradient Descent), yet this method has several limitations. In particular, it relies on the assumption that data-points ... Read more
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BIU learning club – Moshe Eliasof – Improving Graph Neural Networks with Learnable Propagation Operators
BIU learning club – Moshe Eliasof – Improving Graph Neural Networks with Learnable Propagation Operators
Location:Engineering building (1103), room 329Title:Improving Graph Neural Networks with Learnable Propagation OperatorsAbstract:Graph Neural Networks (GNNs) are limited in their propagation operators. In many cases, these operators often contain non-negative elements only and are shared across channels, limiting the expressiveness of GNNs. Moreover, some GNNs suffer from over-smoothing, limiting their depth. On the other hand, Convolutional ... Read more
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BIU learning club – Shalev Shaer – Betting as a mechanism to make reliable discoveries
BIU learning club – Shalev Shaer – Betting as a mechanism to make reliable discoveries
Zoom link: https://biu-ac-il.zoom.us/j/4685913265 Title:Betting as a mechanism to make reliable discoveries Abstract:This talk introduces a new statistical testing framework that allows researchers to analyze an incoming i.i.d. data stream with any arbitrary dependency structure, and safely conclude whether a feature is conditionally associated with the response under study. We allow the processing of data points online, as soon ... Read more