5 papers · 1 filter
Mini-Hes: A Parallelizable Second-order Latent Factor Analysis Model
Jialiang Wang, Weiling Li, Yurong Zhong +1
Interactions among large number of entities is naturally high-dimensional and incomplete (HDI) in many big data related tasks. Behavioral characteristics of users are hidden in the…
Proximal Symmetric Non-negative Latent Factor Analysis: A Novel Approach to Highly-Accurate Representation of Undirected Weighted Networks
Yurong Zhong, Zhe Xie, Weiling Li +1
An Undirected Weighted Network (UWN) is commonly found in big data-related applications. Note that such a network's information connected with its nodes, and edges can be expressed…
Incoporating Weighted Board Learning System for Accurate Occupational Pneumoconiosis Staging
Kaiguang Yang, Yeping Wang, Qianhao Luo +2
Occupational pneumoconiosis (OP) staging is a vital task concerning the lung healthy of a subject. The staging result of a patient is depended on the staging standard and his chest…
A Practical Second-order Latent Factor Model via Distributed Particle Swarm Optimization
Jialiang Wang, Yurong Zhong, Weiling Li
Latent Factor (LF) models are effective in representing high-dimension and sparse (HiDS) data via low-rank matrices approximation. Hessian-free (HF) optimization is an efficient me…
An Unconstrained Symmetric Nonnegative Latent Factor Analysis for Large-scale Undirected Weighted Networks
Zhe Xie, Weiling Li, Yurong Zhong
Large-scale undirected weighted networks are usually found in big data-related research fields. It can naturally be quantified as a symmetric high-dimensional and incomplete (SHDI)…