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IEEE Transactions on Automatic Control最新文献

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Distributionally Robust Model Predictive Control: Closed-loop Guarantees and Scalable Algorithms 分布式鲁棒模型预测控制：闭环保证和可扩展算法
IF 6.8 1区 计算机科学
IEEE Transactions on Automatic Control Pub Date : 2024-11-14 DOI: 10.1109/tac.2024.3498702
Robert D. McAllister, Peyman Mohajerin Esfahani
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引用次数: 0
Estimating True Beliefs in Opinion Dynamics with Social Pressure 利用社会压力估算舆论动态中的真实信念
IF 6.8 1区 计算机科学
IEEE Transactions on Automatic Control Pub Date : 2024-11-14 DOI: 10.1109/tac.2024.3498693
Jennifer Tang, Aviv Adler, Amir Ajorlou, Ali Jadbabaie
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引用次数: 0
A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent 分布随机梯度下降瞬态时间的一个尖锐估计
IF 6.8 1区 计算机科学
IEEE Transactions on Automatic Control Pub Date : 2021-11-09 DOI: 10.1109/TAC.2021.3126253
Shi Pu;Alex Olshevsky;Ioannis Ch. Paschalidis
{"title":"A Sharp Estimate on the Transient Time of Distributed Stochastic Gradient Descent","authors":"Shi Pu;Alex Olshevsky;Ioannis Ch. Paschalidis","doi":"10.1109/TAC.2021.3126253","DOIUrl":"10.1109/TAC.2021.3126253","url":null,"abstract":"This article is concerned with minimizing the average of \u0000<inline-formula><tex-math>$n$</tex-math></inline-formula>\u0000 cost functions over a network, in which agents may communicate and exchange information with each other. We consider the setting where only noisy gradient information is available. To solve the problem, we study the distributed stochastic gradient descent (DSGD) method and perform a nonasymptotic convergence analysis. For strongly convex and smooth objective functions, in expectation, DSGD asymptotically achieves the optimal network-independent convergence rate compared to centralized stochastic gradient descent. Our main contribution is to characterize the transient time needed for DSGD to approach the asymptotic convergence rate. Moreover, we construct a “hard” optimization problem that proves the sharpness of the obtained result. Numerical experiments demonstrate the tightness of the theoretical results.","PeriodicalId":13201,"journal":{"name":"IEEE Transactions on Automatic Control","volume":"67 11","pages":"5900-5915"},"PeriodicalIF":6.8,"publicationDate":"2021-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9609587","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9619759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 44
Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach 稀疏Volterra系统的辨识：一种几乎正交匹配寻踪方法
IF 6.8 1区 计算机科学
IEEE Transactions on Automatic Control Pub Date : 2021-03-31 DOI: 10.1109/TAC.2021.3070027
Changming Cheng;Er-Wei Bai;Zhike Peng
{"title":"Identification of Sparse Volterra Systems: An Almost Orthogonal Matching Pursuit Approach","authors":"Changming Cheng;Er-Wei Bai;Zhike Peng","doi":"10.1109/TAC.2021.3070027","DOIUrl":"10.1109/TAC.2021.3070027","url":null,"abstract":"This article considers identification of sparse Volterra systems. A method based on the almost orthogonal matching pursuit (AOMP) is proposed. The AOMP algorithm allows one to estimate one nonzero coefficient at a time until all nonzero coefficients are found without losing the optimality and the sparsity, thus avoiding the curse of dimensionality often encountered in Volterra system identification.","PeriodicalId":13201,"journal":{"name":"IEEE Transactions on Automatic Control","volume":"67 4","pages":"2027-2032"},"PeriodicalIF":6.8,"publicationDate":"2021-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TAC.2021.3070027","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9227225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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