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Consensus Driven Learning [article]

Kyle Crandall, Dustin Webb
2020 arXiv   pre-print
This is achieved by taking inspiration from Distributed Averaging Consensus algorithms to coordinate the various nodes.  ...  We show that our coordination method allows models to be learned on highly biased datasets, and in the presence of intermittent communication failure.  ...  In this paper, we propose an algorithm we call a Consensus Learning (CL) algorithm.  ... 
arXiv:2005.10300v1 fatcat:ndh4e7p6qbgqne7u3e72ypvhym

Data Driven Distributed Bipartite Consensus Tracking for nonlinear Multiagent Systems Via Iterative Learning Control

Huarong Zhao, Li Peng, Hongnian Yu
2020 IEEE Access  
Then a data-driven distributed bipartite consensus iterative learning control (DBCILC) algorithm is proposed considering both fixed and switching topologies.  ...  This article explores a data-driven distributed bipartite consensus tracking (DBCT) problem for discrete-time multi-agent systems (MASs) with coopetition networks under repeatable operations.  ...  A Data-driven distributed output consensus control is proposed for MASs, the Learning-based adaptive attitude control is formulated for spacecraft formation to guarantee prescribed performance in [21]  ... 
doi:10.1109/access.2020.3014496 fatcat:4kcothubfnekfctxxqla5u6epm

Learning Backchannel Prediction Model from Parasocial Consensus Sampling: A Subjective Evaluation [chapter]

Lixing Huang, Louis-Philippe Morency, Jonathan Gratch
2010 Lecture Notes in Computer Science  
it is even better than the virtual human driven by real listener's behavior in some cases.  ...  and naturalness, and it is even better than the virtual human driven by real listeners' behavior in some cases.  ...  is driven by the CRF model trained on parasocial consensus.  ... 
doi:10.1007/978-3-642-15892-6_17 fatcat:rc2ik4jz7bgzzo7kalnnixq32a

Personal learning environments and university teacher roles explored using Delphi

Zaffar Ahmed Shaikh, Shakeel Ahmed Khoja
2014 Australasian Journal of Educational Technology  
learning environments (PLEs).  ...  The study concluded by identifying the 28 roles on which the Delphi panel was able to reach a consensus.  ...  Delphi method: Building consensus on university teacher roles for PLE-driven pedagogy Delphi is a research-based collaborative problem-solving technique.  ... 
doi:10.14742/ajet.324 fatcat:gudoht4kvve7hcgfzybjd3tt6m

Parallel-Education-Blockchain Driven Smart Education: Challenges and Issues

Xiaoyan Gong, Xiwei Liu, Sifeng Jing, Gang Xiong, Jiehan Zhou
2018 2018 Chinese Automation Congress (CAC)  
Recently education blockchain driven smart education has become focus of attention, and related system frameworks and key technologies are presented.  ...  paper first introduces education blockchain, challenges and issues, then based on introduction of parallel intelligence theory and parallel blockchain, it proposes parallel education blockchain, and its driven  ...  PARALLEL WHOLE-EDU DRIVEN INTELLIGENT EDUCATION Functional model of parallel Whole-Edu-driven smart education is shown in Figure 4 .  ... 
doi:10.1109/cac.2018.8623198 fatcat:skap7bgpnbeatoofmfzlsmyyae

Deep-learning aided consensus problem constrained by network-centrality

Shoya Ogawa, Koji Ishii
2022 IEICE Communications Express  
The deep-learning aided parameter optimization method for the average consensus problem with a complex network has been proposed by Kishida et al., which can significantly accelerate its convergence performance  ...  Deep-learning aided average consensus problem This section introduces the fundamentals of consensus problem [4] and deep-learning aided average consensus problem proposed in [2] .  ...  focused network (2) consensus with the time-variant weighting factors optimized by the data-driven approach [2] .  ... 
doi:10.1587/comex.2021xbl0182 fatcat:oi7u4vo2dfhkpa6lttbzkto2fq

Table of contents

2020 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS)  
Xinyu Zhao, Na Qin, Jie Huang, Yongchen Miao 272 Consensus Tracking for Discrete Distributed Parameter Multi-agent Systems via Iterative Learning Control………………………………...  ...  …Bei Liu, Kene Li, Zeng Zhang, Qiaoliang Mo, Xisheng Dai, Hongtao Ye 684 Event-driven Distributed Kalman-consensus Filter with Limited Memory Information …………...……………………………………………………………….  ...  Proceedings of 2020 IEEE 9th Data Driven Control and Learning Systems Conference November 20-22, 2020, Liuzhou, China  ... 
doi:10.1109/ddcls49620.2020.9275156 fatcat:kl3b4ptikjhzjn6p7eoqcmwypa

Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

Chao Yu, Guozhen Tan, Hongtao Lv, Zhen Wang, Jun Meng, Jianye Hao, Fenghui Ren
2016 Scientific Reports  
A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social  ...  This kind of experience-based learning is an essential capability of human and plays a  ...  As can be seen, the performance-driven approach outperforms the behaviour-driven approach in terms of a higher level of convergence and a faster convergence speed.  ... 
doi:10.1038/srep27626 pmid:27282089 pmcid:PMC4901282 fatcat:66bhzatayjeohjtm3rvkarj73a

Deep-Learning Based Linear Average Consensus for Faster Convergence over Temporal Network [article]

Masako Kishida, Masaki Ogura, Tadashi Wadayama
2019 arXiv   pre-print
We specifically present a data-driven methodology for tuning the weights of temporal (i.e., time-varying) networks by using deep learning techniques.  ...  We then train the neural network by using standard deep learning technique to minimize the consensus error over a given finite time-horizon.  ...  We then describe our data-driven methodology for tuning the weights of the network, in which we apply the techniques in the deep-learning to the signal flow graph obtained by unfolding the consensus algorithm  ... 
arXiv:1908.09963v1 fatcat:qzhtlkcyojfl7kkd6wu23zmsxi

Data-Driven Distributed State Estimation and Behavior Modeling in Sensor Networks [article]

Rui Yu, Zhenyuan Yuan, Minghui Zhu, Zihan Zhou
2020 arXiv   pre-print
Second, the objects' movement behavior is unknown, and needs to be learned using sensor observations.  ...  In this work, for the first time, we formally formulate the problem of simultaneous state estimation and behavior learning in a sensor network.  ...  But unlike existing consensus filters which assume known state transition and observation models, we study data-driven approaches to learn such models. C.  ... 
arXiv:2009.10827v2 fatcat:adghsmwqrvd43j3l3td3ilqwie

Blockchain and artificial intelligence for network security

Diogo Menezes Ferrazani Mattos, Francine Krief, Sandra Julieta Rueda
2020 Annales des télécommunications  
As a consequence, artificial intelligence and machine learning techniques experience significant improvements and emerge as enabling technologies for the next-generation networks.  ...  This issue's papers cover a wide range of topics, such as new cryptographic models applied to healthcare, intelligent threat-detection systems, and new consensus mechanisms for the blockchain.  ...  This special edition is dedicated to these new technologies that shape the world to have more reliable computer networks while enabling new distributed and knowledge-driven security applications and services  ... 
doi:10.1007/s12243-020-00754-7 fatcat:t3ikdhi7wjbcdhuhbsgoflh7fe

University of Glasgow at TREC 2011: Experiments with Terrier in Crowdsourcing, Microblog, and Web Tracks

Richard McCreadie, Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis
2011 Text Retrieval Conference  
For the Web track, we enhance the data-driven learning support within Terrier by proposing a novel framework for the fast computation of document features for learning to rank.  ...  Meanwhile, we continue to build upon our novel xQuAD framework and data-driven ranking approaches within Terrier to achieve effective and efficient ranking for the TREC Web track.  ...  For our participation in the consensus task, we propose a data-driven approach that learns a model for consensus calculation.  ... 
dblp:conf/trec/McCreadieMSO11 fatcat:gdi4zp7ozvbmdmur7h6tznuri4

Deep Learning-Based Average Consensus

Masako Kishida, Masaki Ogura, Yuichi Yoshida, Tadashi Wadayama
2020 IEEE Access  
We propose a data-driven approach to tuning the weights of temporal (i.e., timevarying) networks using deep learning techniques.  ...  The edge weights of the obtained neural network are then trained using standard deep learning techniques to minimize consensus error over a given finite-time window.  ...  In the next subsection, we describe our data-driven approach to tuning edge weights using deep learning techniques.  ... 
doi:10.1109/access.2020.3014148 fatcat:kxwne4fjunfk7mto6aphqlh5iq

Consensual Cooperative-Learning: A New Method to Harmonize the Learning of Complex Knowledge

M.Dahmani Fathallah, Sayed H. Rajab, Hashem A. Al Musawi, Aisha Al Foderi, Farah Al Qabandi, Fatma Al Saad, Haya Al Kanderi, Mashail Al Obaid, Samar Al Abyoki, Fuad Al Habeeb, Fuad Al Hassan, Hameeda Al Maalki (+4 others)
2018 American Journal of Educational Research  
To fill this educational gap, we developed an incrementally innovative learning-centered method; the consensual cooperativelearning method (CCL) and tested it on a group of executives enrolled in an innovation  ...  No teaching method is currently available, however, about achieving a harmonized learning outcome of puzzling knowledge.  ...  The three stages are as follows: Individual self-learning, Cooperative self-learning and Discussion-driven harmonized learning.  ... 
doi:10.12691/education-6-12-18 fatcat:mk5qc6syzndbvgeqrnxzz4yrmm

Video-based consensus annotations for learning: A feasibility study

Samuel Dodson, Luanne Freund, Dongwook Yoon, Matthew Fong, Rick Kopak, Sidney Fels
2018 Proceedings of the Association for Information Science and Technology  
Our results show that consensus annotations-the video content that has received attention from many students-may be a feasible, data-driven way to flag information for use by subsequent learners.  ...  Video-based learning is increasingly common in higher education; however, the video players available make limited use of logged interaction data to support and guide students' viewing.  ...  INTRODUCTION Video-based learning is increasingly popular in higher education; however, most video players provide students with limited tools for learning.  ... 
doi:10.1002/pra2.2018.14505501119 fatcat:yfrhj3wwuvhk7c2bttjiik2ebu
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