Exploiting geometric structure in (matrix-valued) optimization

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A Stochastic Newton Algorithm for Distributed Convex Optimization

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Hitting the High-D(imensional) Notes: An ODE for SGD learning dynamics in high-dimensions

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Beyond NTK: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time

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Theoretical and Practical Insights from Linear Transformers

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Robust Gradient Descent: Agnostically Estimating an Unknown Affine Transformation with Near-optimal Error

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Randomized Linear Algebra for Interior Point Methods

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IPM and Nested Dissection for Planar and Separable LPs

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Nash Social Welfare and A Tale of Mathematical Programs

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Short-Flat Decompositions and Faster Algorithms for Linear Inverse Problems

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