Dear all,
Next week, we have the pleasure of having Prof. Gal Chechik give a talk in the colloquium.
The seminar will be held on Monday, February 19th, at 14:00. Location: C220.
The title, abstract and bio appear below.
Looking forward to seeing you, Sagie and Liat
*Title:* Personalizing foundation models for visual generative AI
*Abstract:* Machine learning now heavily relies on "foundation models", representations trained with massive data in a task-agnostic way, and then used for downstream tasks. But how can we make them most useful for our own tasks? I will discuss a series of studies addressing this problem in the context of vision-and-language models. These include textual-inversion techniques - where we teach new personalized visual concepts to the model that can be combined with known concepts, and ways to improve their editability and speed. I will also discuss generation of rare classes, personalized approaches to discriminative problems, and future directions in model personalization.
*Bio*: Gal Chechik is a Professor at Bar-Ilan University and a senior director of AI research at NVIDIA. His current research focuses on learning for reasoning and perception. In 2018, Gal joined NVIDIA to found and head nvidia's research in Israel. Prior to that, Gal was a staff research scientist at Google Brain and Google research developing large-scale algorithms for machine perception, used by millions daily. Gal earned his PhD in 2004 from the Hebrew University, and completed his postdoctoral training at Stanford CS department. Gal authored ~130 refereed publications, ~50 patents, including publications in Nature Biotechnology, Cell and PNAS. His work won awards at ICML and NeurIPS. http://chechiklab.biu.ac.il , publications https://scholar.google.com/citations?hl=en&user=Wk2gAZUAAAAJ
Reminder, this is happening today.
On Wed, Feb 14, 2024 at 6:58 AM Sagie Benaim sagie.benaim@mail.huji.ac.il wrote:
Dear all,
Next week, we have the pleasure of having Prof. Gal Chechik give a talk in the colloquium.
The seminar will be held on Monday, February 19th, at 14:00. Location: C220.
The title, abstract and bio appear below.
Looking forward to seeing you, Sagie and Liat
*Title:* Personalizing foundation models for visual generative AI
*Abstract:* Machine learning now heavily relies on "foundation models", representations trained with massive data in a task-agnostic way, and then used for downstream tasks. But how can we make them most useful for our own tasks? I will discuss a series of studies addressing this problem in the context of vision-and-language models. These include textual-inversion techniques - where we teach new personalized visual concepts to the model that can be combined with known concepts, and ways to improve their editability and speed. I will also discuss generation of rare classes, personalized approaches to discriminative problems, and future directions in model personalization.
*Bio*: Gal Chechik is a Professor at Bar-Ilan University and a senior director of AI research at NVIDIA. His current research focuses on learning for reasoning and perception. In 2018, Gal joined NVIDIA to found and head nvidia's research in Israel. Prior to that, Gal was a staff research scientist at Google Brain and Google research developing large-scale algorithms for machine perception, used by millions daily. Gal earned his PhD in 2004 from the Hebrew University, and completed his postdoctoral training at Stanford CS department. Gal authored ~130 refereed publications, ~50 patents, including publications in Nature Biotechnology, Cell and PNAS. His work won awards at ICML and NeurIPS. http://chechiklab.biu.ac.il , publications https://scholar.google.com/citations?hl=en&user=Wk2gAZUAAAAJ
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Sagie Benaim