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#machine learning Preprint Oct 2026

Exact Dynamics and Finite-Sample Trajectory Recovery of Linear Recursive Feature Machines

Recursive feature machines (RFMs) learn representations of data by alternating between fitting a predictor to a dataset and updating features of that predictor using the average gradient outer product (AGOP). Connections between AGOPs and feature learning in neural networks motivate linear RFMs as a simple setting for...

Andrew Cheng, B. Kiani, Yue M. Lu et al. · 0 citations
Preprint Oct 2026

Quantitative Universality of Approximate Message Passing for Rank-One Quadratic Sensing

Approximate Message Passing (AMP) algorithms are attractive as they are computationally efficient and simultaneously admit a precise characterization in terms of the low-dimensional"state-evolution"recursion. In this work, we establish quantitative universality for AMP with centered rank-one sensing matrices $Z_i=(x_ix...

Duy Thuc Nguyen, Yue M. Lu, Subhabrata Sen · 0 citations

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