13 citations · 36 across the 13 of their papers we have counts for
13 papers
Coexistence of multiuser entanglement distribution and classical light in optical fiber network with a semiconductor chip
Xu Jing, Cheng Qian, Hu Nian +10
Building communication links among multiple users in a scalable and robust way is a key objective in achieving large-scale quantum networks. In realistic scenario, noise from the c…
DeCom: Deep Coupled-Factorization Machine for Post COVID-19 Respiratory Syncytial Virus Prediction with Nonpharmaceutical Interventions Awareness
Xinyan Li, Cheng Qian, Lucas Glass
Respiratory syncytial virus (RSV) is one of the most dangerous respiratory diseases for infants and young children. Due to the nonpharmaceutical intervention (NPI) imposed in the C…
GOCPT: Generalized Online Canonical Polyadic Tensor Factorization and Completion
Chaoqi Yang, Cheng Qian, Jimeng Sun
Low-rank tensor factorization or completion is well-studied and applied in various online settings, such as online tensor factorization (where the temporal mode grows) and online t…
Clinical trial site matching with improved diversity using fair policy learning
Rakshith S Srinivasa, Cheng Qian, Brandon Theodorou +4
The ongoing pandemic has highlighted the importance of reliable and efficient clinical trials in healthcare. Trial sites, where the trials are conducted, are chosen mainly based on…
JULIA: Joint Multi-linear and Nonlinear Identification for Tensor Completion
Cheng Qian, Kejun Huang, Lucas Glass +2
Tensor completion aims at imputing missing entries from a partially observed tensor. Existing tensor completion methods often assume either multi-linear or nonlinear relationships…
MTC: Multiresolution Tensor Completion from Partial and Coarse Observations
Chaoqi Yang, Navjot Singh, Cao Xiao +3
Existing tensor completion formulation mostly relies on partial observations from a single tensor. However, tensors extracted from real-world data are often more complex due to: (i…
ATD: Augmenting CP Tensor Decomposition by Self Supervision
Chaoqi Yang, Cheng Qian, Navjot Singh +4
Tensor decompositions are powerful tools for dimensionality reduction and feature interpretation of multidimensional data such as signals. Existing tensor decomposition objectives…
Multi-version Tensor Completion for Time-delayed Spatio-temporal Data
Cheng Qian, Nikos Kargas, Cao Xiao +3
Real-world spatio-temporal data is often incomplete or inaccurate due to various data loading delays. For example, a location-disease-time tensor of case counts can have multiple d…
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization
Nikos Kargas, Cheng Qian, Nicholas D. Sidiropoulos +3
Accurate prediction of the transmission of epidemic diseases such as COVID-19 is crucial for implementing effective mitigation measures. In this work, we develop a tensor method to…
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Ardavan Afshar, Kejing Yin, Sherry Yan +4
Existing tensor factorization methods assume that the input tensor follows some specific distribution (i.e. Poisson, Bernoulli, and Gaussian), and solve the factorization by minimi…
STAN: Spatio-Temporal Attention Network for Pandemic Prediction Using Real World Evidence
Junyi Gao, Rakshith Sharma, Cheng Qian +5
Objective: The COVID-19 pandemic has created many challenges that need immediate attention. Various epidemiological and deep learning models have been developed to predict the COVI…
REP: Predicting the Time-Course of Drug Sensitivity
Cheng Qian, Amin Emad, Nicholas D. Sidiropoulos
The biological processes involved in a drug's mechanisms of action are oftentimes dynamic, complex and difficult to discern. Time-course gene expression data is a rich source of in…
From Gene Expression to Drug Response: A Collaborative Filtering Approach
Cheng Qian, Nicholas D. Sidiropoulos, Magda Amiridi +1
Predicting the response of cancer cells to drugs is an important problem in pharmacogenomics. Recent efforts in generation of large scale datasets profiling gene expression and dru…