1 code implementation • 5 Jun 2023 • Shahana Ibrahim, Tri Nguyen, Xiao Fu
The contribution of this work is twofold: First, performance guarantees of the CCEM criterion are presented.
1 code implementation • 5 Jun 2023 • Shahana Ibrahim, Xiao Fu, Rebecca Hutchinson, Eugene Seo
Systematic under-counting effects are observed in data collected across many disciplines, e. g., epidemiology and ecology.
1 code implementation • 30 May 2023 • Tri Nguyen, Shahana Ibrahim, Xiao Fu
The recent integration of deep learning and pairwise similarity annotation-based constrained clustering -- i. e., $\textit{deep constrained clustering}$ (DCC) -- has proven effective for incorporating weak supervision into massive data clustering: Less than 1% of pair similarity annotations can often substantially enhance the clustering accuracy.
no code implementations • 14 Jun 2021 • 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 labeling massive data.
no code implementations • 29 Apr 2021 • Wenqiang Pu, Shahana Ibrahim, Xiao Fu, Mingyi Hong
This work offers a unified stochastic algorithmic framework for large-scale CPD decomposition under a variety of non-Euclidean loss functions.
1 code implementation • 25 Nov 2020 • Shahana Ibrahim, Xiao Fu
This work aims at learning mixed membership of nodes using queried edges.
no code implementations • 30 Jun 2020 • Shahana Ibrahim, Xiao Fu
Recent work has proposed to recover the joint probability mass function (PMF) of an arbitrary number of RVs from three-dimensional marginals, leveraging the algebraic properties of low-rank tensor decomposition and the (unknown) dependence among the RVs.
no code implementations • 8 Jan 2020 • Shahana Ibrahim, Xiao Fu, Xingguo Li
Our interest lies in the recoverability properties of compressed tensors under the \textit{canonical polyadic decomposition} (CPD) model.
no code implementations • NeurIPS 2019 • Shahana Ibrahim, Xiao Fu, Nikos Kargas, Kejun Huang
The data deluge comes with high demands for data labeling.
no code implementations • 16 Jan 2019 • Xiao Fu, Shahana Ibrahim, Hoi-To Wai, Cheng Gao, Kejun Huang
In this work, we propose a stochastic optimization framework for large-scale CPD with constraints/regularizations.