Gaussian Process Decentralized Data Fusion Meets Transfer Learning in Large-Scale Distributed Cooperative Perception

11/16/2017
by   Ruofei Ouyang, et al.
0

This paper presents novel Gaussian process decentralized data fusion algorithms exploiting the notion of agent-centric support sets for distributed cooperative perception of large-scale environmental phenomena. To overcome the limitations of scale in existing works, our proposed algorithms allow every mobile sensing agent to choose a different support set and dynamically switch to another during execution for encapsulating its own data into a local summary that, perhaps surprisingly, can still be assimilated with the other agents' local summaries (i.e., based on their current choices of support sets) into a globally consistent summary to be used for predicting the phenomenon. To achieve this, we propose a novel transfer learning mechanism for a team of agents capable of sharing and transferring information encapsulated in a summary based on a support set to that utilizing a different support set with some loss that can be theoretically bounded and analyzed. To alleviate the issue of information loss accumulating over multiple instances of transfer learning, we propose a new information sharing mechanism to be incorporated into our algorithms in order to achieve memory-efficient lazy transfer learning. Empirical evaluation on real-world datasets show that our algorithms outperform the state-of-the-art methods.

READ FULL TEXT

page 2

page 13

page 14

research
08/09/2014

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

The problem of modeling and predicting spatiotemporal traffic phenomena ...
research
02/12/2018

Gaussian Process Classification with Privileged Information by Soft-to-Hard Labeling Transfer

Learning using privileged information is an attractive problem setting t...
research
09/13/2020

Rumor-robust Decentralized Gaussian Process Learning, Fusion, and Planning for Modeling Multiple Moving Targets

This paper presents a decentralized Gaussian Process (GP) learning, fusi...
research
09/19/2023

Resource-Efficient Cooperative Online Scalar Field Mapping via Distributed Sparse Gaussian Process Regression

Cooperative online scalar field mapping is an important task for multi-r...
research
11/11/2020

Transferred Fusion Learning using Skipped Networks

Identification of an entity that is of interest is prominent in any inte...
research
05/08/2021

Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction

Modern data analytics take advantage of ensemble learning and transfer l...

Please sign up or login with your details

Forgot password? Click here to reset