27 citations · 101 across the 25 of their papers we have counts for
7 papers · 1 filter
A Framework for Generalizing Critical Heat Flux Detection Models Using Unsupervised Image-to-Image Translation
Firas Al-Hindawi, Tejaswi Soori, Han Hu +4
The detection of critical heat flux (CHF) is crucial in heat boiling applications as failure to do so can cause rapid temperature ramp leading to device failures. Many machine lear…
The Second Competition on Spatial Statistics for Large Datasets
Sameh Abdulah, Faten Alamri, Pratik Nag +4
In the last few decades, the size of spatial and spatio-temporal datasets in many research areas has rapidly increased with the development of data collection technologies. As a re…
Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology
Yan Huang, Ying Sun, Zehan Zhu +2
We develop a general framework unifying several gradient-based stochastic optimization methods for empirical risk minimization problems both in centralized and distributed scenario…
Cohomology algebra of orbit spaces of free involutions on the product of projective space and 4-sphere
Ying Sun, Jianbo Wang
Let be a finitistic space with the mod 2 cohomology of the product space of a projective space and a 4-sphere. Assume that admits a free involution. In this paper we study…
Bone marrow sparing for cervical cancer radiotherapy on multimodality medical images
Yuening Wang, Ying Sun, Jie Yuan +4
Cervical cancer threatens the health of women seriously. Radiotherapy is one of the main therapy methods but with high risk of acute hematologic toxicity. Delineating the bone marr…
Modeling and Predicting Spatio-temporal Dynamics of PM Concentrations Through Time-evolving Covariance Models
Ghulam A. Qadir, Ying Sun
Fine particulate matter (PM) has become a great concern worldwide due to its adverse health effects. PM concentrations typically exhibit complex spatio-temporal var…
Decentralized Sparse Linear Regression via Gradient-Tracking: Linear Convergence and Statistical Guarantees
Marie Maros, Gesualdo Scutari, Ying Sun +1
We study sparse linear regression over a network of agents, modeled as an undirected graph and no server node. The estimation of the -sparse parameter is formulated as a constra…