activity
20152020
most citedOptimal Estimation with Limited Measurements and Noisy Communication

23 citations · 27 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2020

A Spherical Hidden Markov Model for Semantics-Rich Human Mobility Modeling

Wanzheng Zhu, Chao Zhang, Shuochao Yao +2

We study the problem of modeling human mobility from semantic trace data, wherein each GPS record in a trace is associated with a text message that describes the user's activity. E…

eess.SY2018★ 1 cited

On Remote Estimation with Multiple Communication Channels

Xiaobin Gao, Emrah Akyol, Tamer Basar

This paper considers a sequential sensor scheduling and remote estimation problem with multiple communication channels. Departing from the classical remote estimation paradigm, whi…

math.OC2016

Optimal Communication Scheduling and Remote Estimation over an Additive Noise Channel

Xiaobin Gao, Emrah Akyol, Tamer Basar

This paper considers a sequential sensor scheduling and remote estimation problem with one sensor and one estimator. The sensor makes sequential observations about the state of an…

eess.SY2015★ 2 cited

Optimal Sensor Scheduling and Remote Estimation over an Additive Noise Channel

Xiaobin Gao, Emrah Akyol, Tamer Basar

We consider a sensor scheduling and remote estimation problem with one sensor and one estimator. At each time step, the sensor makes an observation on the state of a source, and th…

cs.IT2015★ 1 cited

On Remote Estimation with Multiple Communication Channels

Xiaobin Gao, Emrah Akyol, Tamer Basar

This paper considers a sequential estimation and sensor scheduling problem in the presence of multiple communication channels. As opposed to the classical remote estimation problem…

eess.SY2015★ 23 cited

Optimal Estimation with Limited Measurements and Noisy Communication

Xiaobin Gao, Emrah Akyol, Tamer Basar

This paper considers a sequential estimation and sensor scheduling problem with one sensor and one estimator. The sensor makes sequential observations about the state of an underly…