1.7k citations · 3.1k across the 23 of their papers we have counts for
5 papers · 1 filter
Hyperspectral Super-resolution: A Coupled Nonnegative Block-term Tensor Decomposition Approach
Guoyong Zhang, Xiao Fu, Kejun Huang +1
Hyperspectral super-resolution (HSR) aims at fusing a hyperspectral image (HSI) and a multispectral image (MSI) to produce a super-resolution image (SRI). Recently, a coupled tenso…
Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms
Shahana Ibrahim, Xiao Fu, Nikos Kargas +1
The data deluge comes with high demands for data labeling. Crowdsourcing (or, more generally, ensemble learning) techniques aim to produce accurate labels via integrating noisy, no…
SNAP: Finding Approximate Second-Order Stationary Solutions Efficiently for Non-convex Linearly Constrained Problems
Songtao Lu, Meisam Razaviyayn, Bo Yang +2
This paper proposes low-complexity algorithms for finding approximate second-order stationary points (SOSPs) of problems with smooth non-convex objective and linear constraints. Wh…
Learning Nonlinear Mixtures: Identifiability and Algorithm
Bo Yang, Xiao Fu, Nicholas D. Sidiropoulos +1
Linear mixture models have proven very useful in a plethora of applications, e.g., topic modeling, clustering, and source separation. As a critical aspect of the linear mixture mod…
Block-Randomized Stochastic Proximal Gradient for Low-Rank Tensor Factorization
Xiao Fu, Shahana Ibrahim, Hoi-To Wai +2
This work considers the problem of computing the canonical polyadic decomposition (CPD) of large tensors. Prior works mostly leverage data sparsity to handle this problem, which is…