3 papers
cs.LG2026
Nearly Optimal Bayesian Inference for Structural Missingness
Chen Liang, Donghua Yang, Yutong Zhao +9
Structural missingness breaks 'just impute and train': values can be undefined by causal or logical constraints, and the mask may depend on observed variables, unobserved variables…
cs.LG2025
Adaptive Data Selection for Multi-Layer Perceptron Training: A Sub-linear Value-Driven Method
Xiyang Zhang, Chen Liang, Haoxuan Qiu +1
Data selection is one of the fundamental problems in neural network training, particularly for multi-layer perceptrons (MLPs) where identifying the most valuable training samples f…
cs.DB2025
Revisiting Data Analysis with Pre-trained Foundation Models
Chen Liang, Donghua Yang, Zheng Liang +6
Data analysis focuses on harnessing advanced statistics, programming, and machine learning techniques to extract valuable insights from vast datasets. An increasing volume and vari…