most citedParallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations

24 citations · 55 across the 3 of their papers we have counts for

collaborators

5 papers

eess.SY2019

Distributed Global Output-Feedback Control for a Class of Euler-Lagrange Systems

Qingkai Yang, Hao Fang, Jie Chen +2

This published paper investigates the distributed tracking control problem for a class of Euler-Lagrange multi-agent systems when the agents can only measure the positions. In this…

math.OC20191 cited

Distributed Solver for Discrete-Time Lyapunov Equations Over Dynamic Networks with Linear Convergence Rate

Xia Jiang, Xianlin Zeng, Jian Sun +1

This paper investigates the problem of solving discrete-time Lyapunov equations (DTLE) over a multi-agent system, where every agent has access to its local information and communic…

cs.LG201424 cited

Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations

Jie Chen, Nannan Cao, Kian Hsiang Low +3

Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-t…

cs.AI201415 cited

Decentralized Data Fusion and Active Sensing with Mobile Sensors for Modeling and Predicting Spatiotemporal Traffic Phenomena

Jie Chen, Kian Hsiang Low, Colin Keng-Yan Tan +4

The problem of modeling and predicting spatiotemporal traffic phenomena over an urban road network is important to many traffic applications such as detecting and forecasting conge…

cs.RO201416 cited

GP-Localize: Persistent Mobile Robot Localization using Online Sparse Gaussian Process Observation Model

Nuo Xu, Kian Hsiang Low, Jie Chen +2

Central to robot exploration and mapping is the task of persistent localization in environmental fields characterized by spatially correlated measurements. This paper presents a Ga…