Newsroom
statistical inference
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S&DS Seminar: Adam Block (Columbia), “Scaling Inference-Time Compute: From Self-Improvement to Pessimism”
Abstract: Language models increasingly rely on scaling inference-time computation to achieve state-of-the-art performance on a growing number of reasoning tasks. A popular paradigm for […]
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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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FDS Colloquium: Houman Owhadi (Caltech), “Co-discovering graphical structure and functional relationships within data: A Gaussian Process framework for connecting the dots”
Abstract: Most scientific challenges can be framed into one of the following three levels of complexity of function approximation. Examples of Type 2 problems include […]
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Workshop Honoring Andrew Barron: Forty Years at the Interplay of Information Theory, Probability and Statistical Learning (Day 3)
The Workshop Honoring Andrew Barron: “Forty Years at the Interplay of Information Theory, Probability and Statistical Learning” will take place from Friday, April 26 […]
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Workshop Honoring Andrew Barron: Forty Years at the Interplay of Information Theory, Probability and Statistical Learning (Day 2)
The Workshop Honoring Andrew Barron: “Forty Years at the Interplay of Information Theory, Probability and Statistical Learning” will take place from Friday, April 26 […]
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Workshop Honoring Andrew Barron: Forty Years at the Interplay of Information Theory, Probability and Statistical Learning
The Workshop Honoring Andrew Barron: “Forty Years at the Interplay of Information Theory, Probability and Statistical Learning” will take place from Friday, April 26 […]