14 citations · 28 across the 5 of their papers we have counts for
5 papers
Variance Regularization for Accelerating Stochastic Optimization
Tong Yang, Long Sha, Pengyu Hong
While nowadays most gradient-based optimization methods focus on exploring the high-dimensional geometric features, the random error accumulated in a stochastic version of any algo…
A Deep Learning Approach for COVID-19 Trend Prediction
Tong Yang, Long Sha, Justin Li +1
In this work, we developed a deep learning model-based approach to forecast the spreading trend of SARS-CoV-2 in the United States. We implemented the designed model using the Unit…
NagE: Non-Abelian Group Embedding for Knowledge Graphs
Tong Yang, Long Sha, Pengyu Hong
We demonstrated the existence of a group algebraic structure hidden in relational knowledge embedding problems, which suggests that a group-based embedding framework is essential f…
Improved Structural Discovery and Representation Learning of Multi-Agent Data
Jennifer Hobbs, Matthew Holbrook, Nathan Frank +2
Central to all machine learning algorithms is data representation. For multi-agent systems, selecting a representation which adequately captures the interactions among agents is ch…
Fine-Grained Retrieval of Sports Plays using Tree-Based Alignment of Trajectories
Long Sha, Patrick Lucey, Stephan Zheng +3
We propose a novel method for effective retrieval of multi-agent spatiotemporal tracking data. Retrieval of spatiotemporal tracking data offers several unique challenges compared t…