activity
20222024
most citedLaplacian-based Cluster-Contractive t-SNE for High Dimensional Data Visualization

3 citations · 7 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2024

Non-Convex Tensor Recovery from Local Measurements

Tongle Wu, Ying Sun, Jicong Fan

Motivated by the settings where sensing the entire tensor is infeasible, this paper proposes a novel tensor compressed sensing model, where measurements are only obtained from sens…

cs.LG20241 cited

Federated t-SNE and UMAP for Distributed Data Visualization

Dong Qiao, Xinxian Ma, Jicong Fan

High-dimensional data visualization is crucial in the big data era and these techniques such as t-SNE and UMAP have been widely used in science and engineering. Big data, however,…

cs.LG2024

Multi-Subspace Matrix Recovery from Permuted Data

Liangqi Xie, Jicong Fan

This paper aims to recover a multi-subspace matrix from permuted data: given a matrix, in which the columns are drawn from a union of low-dimensional subspaces and some columns are…

cs.LG2024

Unsupervised Anomaly Detection for Tabular Data Using Noise Evaluation

Wei Dai, Kai Hwang, Jicong Fan

Unsupervised anomaly detection (UAD) plays an important role in modern data analytics and it is crucial to provide simple yet effective and guaranteed UAD algorithms for real appli…

cs.LG2024

K-means Derived Unsupervised Feature Selection using Improved ADMM

Ziheng Sun, Chris Ding, Jicong Fan

Feature selection is important for high-dimensional data analysis and is non-trivial in unsupervised learning problems such as dimensionality reduction and clustering. The goal of…

cs.LG2024

Graph Classification via Reference Distribution Learning: Theory and Practice

Zixiao Wang, Jicong Fan

Graph classification is a challenging problem owing to the difficulty in quantifying the similarity between graphs or representing graphs as vectors, though there have been a few m…