6 papers
Adaptive Transfer Clustering: A Unified Framework
Yuqi Gu, Zhongyuan Lyu, Kaizheng Wang
We propose a general transfer learning framework for clustering given a main dataset and an auxiliary one about the same subjects. The two datasets may reflect similar but differen…
Spectral Clustering with Likelihood Refinement for High-dimensional Latent Class Recovery
Zhongyuan Lyu, Yuqi Gu
Latent class models are widely used for identifying unobserved subgroups from multivariate categorical data in social sciences, with binary data as a particularly popular example.…
Canonical Intermediate Representation for LLM-based optimization problem formulation and code generation
Zhongyuan Lyu, Shuoyu Hu, Lujie Liu +2
Automatically formulating optimization models from natural language descriptions is a growing focus in operations research, yet current LLM-based approaches struggle with the compo…
Spectral Joint Subspace Estimation for Heterogeneous Multi-View Data: Geometry and Reweighting
Jingyang Li, Zhongyuan Lyu
Many modern datasets consist of multiple related matrices measured on a common set of units, with the goal of recovering a shared low-dimensional subspace. The Angle-based Joint an…
Large-dimensional Factor Analysis with Weighted PCA
Zhongyuan Lyu, Ming Yuan
Principal component analysis (PCA) is arguably the most widely used approach for large-dimensional factor analysis. While it is effective when the factors are sufficiently strong,…
Degree-heterogeneous Latent Class Analysis for High-dimensional Discrete Data
Zhongyuan Lyu, Ling Chen, Yuqi Gu
The latent class model is a widely used mixture model for multivariate discrete data. Besides the existence of qualitatively heterogeneous latent classes, real data often exhibit a…