1 citations · 1 across the 2 of their papers we have counts for
6 papers
Granger Causality Based Hierarchical Time Series Clustering for State Estimation
Sin Yong Tan, Homagni Saha, Margarite Jacoby +2
Clustering is an unsupervised learning technique that is useful when working with a large volume of unlabeled data. Complex dynamical systems in real life often entail data streami…
Cross-Gradient Aggregation for Decentralized Learning from Non-IID data
Yasaman Esfandiari, Sin Yong Tan, Zhanhong Jiang +4
Decentralized learning enables a group of collaborative agents to learn models using a distributed dataset without the need for a central parameter server. Recently, decentralized…
Decentralized Deep Learning using Momentum-Accelerated Consensus
Aditya Balu, Zhanhong Jiang, Sin Yong Tan +3
We consider the problem of decentralized deep learning where multiple agents collaborate to learn from a distributed dataset. While there exist several decentralized deep learning…
Few shot clustering for indoor occupancy detection with extremely low-quality images from battery free cameras
Homagni Saha, Sin Yong Tan, Ali Saffari +3
Reliable detection of human occupancy in indoor environments is critical for various energy efficiency, security, and safety applications. We consider this challenge of occupancy d…
Spatiotemporal Attention for Multivariate Time Series Prediction and Interpretation
Tryambak Gangopadhyay, Sin Yong Tan, Zhanhong Jiang +2
Multivariate time series modeling and prediction problems are abundant in many machine learning application domains. Accurate interpretation of such prediction outcomes from a mach…
On Higher-order Moments in Adam
Zhanhong Jiang, Aditya Balu, Sin Yong Tan +3
In this paper, we investigate the popular deep learning optimization routine, Adam, from the perspective of statistical moments. While Adam is an adaptive lower-order moment based…