3 papers
cs.IT2025
Statistical Limits for Finite-Rank Tensor Estimation
Riccardo Rossetti, Galen Reeves
This paper provides a unified framework for analyzing tensor estimation problems that allow for nonlinear observations, heteroskedastic noise, and covariate information. We study a…
math.ST2024
Linear Operator Approximate Message Passing (OpAMP)
Riccardo Rossetti, Bobak Nazer, Galen Reeves
This paper introduces a framework for approximate message passing (AMP) in dynamic settings where the data at each iteration is passed through a linear operator. This framework is…
stat.ML2023
Approximate Message Passing for the Matrix Tensor Product Model
Riccardo Rossetti, Galen Reeves
We propose and analyze an approximate message passing (AMP) algorithm for the matrix tensor product model, which is a generalization of the standard spiked matrix models that allow…