6 papers
Diagonalized Attention for Individualized Regression: Latent-Row Localization and Prediction
Borui Peng, Liwei Lin, Feifei Wang +1
Modern text and image representations are often matrix-valued, with rows corresponding to tokens, patches, or other local feature vectors. Predictive information is often sparse bu…
Enterprise Profit Prediction Using Multiple Data Sources with Missing Values through Vertical Federated Learning
Huiyun Tang, Feifei Wang, Long Feng +1
Small and medium-sized enterprises (SMEs) play a crucial role in driving economic growth. Monitoring their financial performance and discovering relevant covariates are essential f…
Data Privatization in Vertical Federated Learning with Client-wise Missing Problem
Huiyun Tang, Long Feng, Yang Li +1
Vertical Federated Learning (VFL) often suffers from client-wise missingness, where entire feature blocks from some clients are unobserved, and conventional approaches are vulnerab…
PrAda-GAN: A Private Adaptive Generative Adversarial Network with Bayes Network Structure
Ke Jia, Yuheng Ma, Yang Li +1
We revisit the problem of generating synthetic data under differential privacy. To address the core limitations of marginal-based methods, we propose the Private Adaptive Generativ…
Enhancing Rare Codes via Probability-Biased Directed Graph Attention for Long-Tail ICD Coding
Tianlei Chen, Yuxiao Chen, Yang Li +1
Automated international classification of diseases (ICD) coding aims to assign multiple disease codes to clinical documents and plays a critical role in healthcare informatics. How…
Factor-Assisted Federated Learning for Personalized Optimization with Heterogeneous Data
Feifei Wang, Huiyun Tang, Yang Li
Federated learning is an emerging distributed machine learning framework aiming at protecting data privacy. Data heterogeneity is one of the core challenges in federated learning,…