Ruixin Guo

2 accepted papers

2026

Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss

Xinyu Li, Ruixin Guo, Yang Zhou, Hao Zhou, Ruoming Jin

ICLR 2026poster

Linear autoencoders (LAEs) have gained increasing popularity in recommender systems due to their simplicity and strong empirical performance. Most LAE models, including the Emphasized Denoising Linear Autoencoder (EDLAE) introduced by (Steck, 2020), use quadratic loss during training. However, the o…

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2025

PAC-Bayes Bounds for Multivariate Linear Regression and Linear Autoencoders

Ruixin Guo, Ruoming Jin, Xinyu Li, Yang Zhou

NeurIPS 2025poster

Linear Autoencoders (LAEs) have shown strong performance in state-of-the-art recommender systems. However, this success remains largely empirical, with limited theoretical understanding. In this paper, we investigate the generalizability -- a theoretical measure of model performance in statistical…

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