Structured Conformal Inference for Matrix Completion with Applications to Group Recommender Systems

no code implementations • 26 Apr 2024 • Ziyi Liang, Tianmin Xie, Xin Tong, Matteo Sesia

We develop a conformal inference method to construct joint confidence regions for structured groups of missing entries within a sparsely observed matrix.

Collaborative Filtering Matrix Completion +1

Conformal inference is (almost) free for neural networks trained with early stopping

1 code implementation • 27 Jan 2023 • Ziyi Liang, Yanfei Zhou, Matteo Sesia

Early stopping based on hold-out data is a popular regularization technique designed to mitigate overfitting and increase the predictive accuracy of neural networks.

Multi-class Classification Outlier Detection

Integrative conformal p-values for powerful out-of-distribution testing with labeled outliers

1 code implementation • 23 Aug 2022 • Ziyi Liang, Matteo Sesia, Wenguang Sun

This paper develops novel conformal methods to test whether a new observation was sampled from the same distribution as a reference set.

Locally Adaptive Algorithms for Multiple Testing with Network Structure, with Application to Genome-Wide Association Studies

1 code implementation • 22 Mar 2022 • Ziyi Liang, T. Tony Cai, Wenguang Sun, Yin Xia

Linkage analysis has provided valuable insights to the GWAS studies, particularly in revealing that SNPs in linkage disequilibrium (LD) can jointly influence disease phenotypes.

Transfer Learning