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language models
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S&DS Seminar: Yuting Wei (Pennsylvania), “Transformers Meet In-Context Learning: A Universal Approximation Theory
Abstract: Modern large language models are capable of in-context learning, the ability to perform new tasks at inference time using only a handful of […]
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FDS Colloquium: Kristina Gligoric (Stanford), “Supporting policies and interventions to promote healthy and sustainable habits”
Abstract: Data science tools create new opportunities to assist policy-makers. For example, enabling healthy and sustainable diets is key to addressing preventable diseases and […]
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FDS Colloquium: Song Mei (Berkeley), “Revisiting neural network approximation theory in the age of generative AI”
Optional Zoom link: https://yale.zoom.us/j/97222935172 Abstract: Textbooks on deep learning theory primarily perceive neural networks as universal function approximators. While this classical viewpoint is fundamental, it […]