88 citations · 128 across the 11 of their papers we have counts for
11 papers
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph
Tong Yang, Yifei Wang, Long Sha +2
Knowledge graph (KG) representation learning aims to encode entities and relations into dense continuous vector spaces such that knowledge contained in a dataset could be consisten…
Algebraic Learning: Towards Interpretable Information Modeling
Tong Owen Yang
Along with the proliferation of digital data collected using sensor technologies and a boost of computing power, Deep Learning (DL) based approaches have drawn enormous attention i…
Q-ViT: Fully Differentiable Quantization for Vision Transformer
Zhexin Li, Tong Yang, Peisong Wang +1
In this paper, we propose a fully differentiable quantization method for vision transformer (ViT) named as Q-ViT, in which both of the quantization scales and bit-widths are learna…
Spectral Clustering with Smooth Tiny Clusters
Hengrui Wang, Yubo Zhang, Mingzhi Chen +1
Spectral clustering is one of the most prominent clustering approaches. The distance-based similarity is the most widely used method for spectral clustering. However, people have a…
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…
Entanglement-Embedded Recurrent Network Architecture: Tensorized Latent State Propagation and Chaos Forecasting
Xiangyi Meng, Tong Yang
Chaotic time series forecasting has been far less understood despite its tremendous potential in theory and real-world applications. Traditional statistical/ML methods are ineffici…
QCluster: Clustering Packets for Flow Scheduling
Tong Yang, Jizhou Li, Yikai Zhao +5
Flow scheduling is crucial in data centers, as it directly influences user experience of applications. According to different assumptions and design goals, there are four typical f…
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…
CovidNet: To Bring Data Transparency in the Era of COVID-19
Tong Yang, Kai Shen, Sixuan He +10
Timely, creditable, and fine-granular case information is vital for local communities and individual citizens to make rational and data-driven responses to the COVID-19 pandemic. T…
MetaAnchor: Learning to Detect Objects with Customized Anchors
Tong Yang, Xiangyu Zhang, Zeming Li +2
We propose a novel and flexible anchor mechanism named MetaAnchor for object detection frameworks. Unlike many previous detectors model anchors via a predefined manner, in MetaAnch…