8 citations · 12 across the 7 of their papers we have counts for
6 papers · 1 filter
MDPGT: Momentum-based Decentralized Policy Gradient Tracking
Zhanhong Jiang, Xian Yeow Lee, Sin Yong Tan +5
We propose a novel policy gradient method for multi-agent reinforcement learning, which leverages two different variance-reduction techniques and does not require large batches ove…
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…
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…