43 citations · 77 across the 10 of their papers we have counts for
27 papers
Fast and Structured Block-Term Tensor Decomposition For Hyperspectral Unmixing
Meng Ding, Xiao Fu, Xi-Le Zhao
The block-term tensor decomposition model with multilinear rank- terms (or, the "LL1 tensor decomposition" in short) offers a valuable alternative for hyperspectral un…
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder
Qi Lyu, Xiao Fu
This work focuses on the problem of unraveling nonlinearly mixed latent components in an unsupervised manner. The latent components are assumed to reside in the probability simplex…
Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization
Shahana Ibrahim, Xiao Fu
Unsupervised learning of the Dawid-Skene (D&S) model from noisy, incomplete and crowdsourced annotations has been a long-standing challenge, and is a critical step towards reliably…
Stochastic Block-ADMM for Training Deep Networks
Saeed Khorram, Xiao Fu, Mohamad H. Danesh +2
In this paper, we propose Stochastic Block-ADMM as an approach to train deep neural networks in batch and online settings. Our method works by splitting neural networks into an arb…
StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling
Eugene Seo, Rebecca A. Hutchinson, Xiao Fu +4
This paper focuses on a core task in computational sustainability and statistical ecology: species distribution modeling (SDM). In SDM, the occurrence pattern of a species on a lan…
Learning to Continuously Optimize Wireless Resource In Episodically Dynamic Environment
Haoran Sun, Wenqiang Pu, Minghe Zhu +3
There has been a growing interest in developing data-driven and in particular deep neural network (DNN) based methods for modern communication tasks. For a few popular tasks such a…