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computational learning
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FDS Colloquium: Steven Johnson (MIT), “Co-design of Optics & Inference”
Abstract: Over the past two decades, an explosion in fabrication capabilities for nano-structured optics has coincided with the development of powerful techniques for “inverse […]
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S&DS Seminar: Jingfeng Wu (Berkeley), “Gradient Descent Dominates Ridge: A Statistical View on Implicit Regularization”
Talk summary: A key puzzle in deep learning is how simple gradient methods find generalizable solutions without explicit regularization. This talk discusses the implicit […]
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S&DS Seminar: Zhuoran Yang (Yale), “Unveiling In-Context Learning: Provable Training Dynamics and Feature Learning in Transformers”
Abstract: In-context learning (ICL) is a cornerstone of large language model (LLM) functionality, yet its theoretical foundations remain elusive due to the complexity of transformer […]
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Computational Biology & Biomedical Informatics (CBB) and Biomedical Informatics & Data Science (BIDS) Project Match
Computational Biology and Biomedical Informatics (CBB) and Biomedical Informatics & Data Science (BIDS) faculty will give 5–7-minute presentations on their research to recruit MS/PhD students […]
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Yale Theory Student Seminar: Alkis Kalavasis, “Some Open Problems in TCS”
Abstract: “Overview of the things I am interested in (Machine Learning & Optimization)” Question 1 (TCS): Query Complexity of MaxCut and beyond. Question 2 […]