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1. www.web.stanford.edu › ~boyd › papersStephen P. Boyd – Papers & Talks - Stanford University

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   Vor 6 Tagen · Stephen P. Boyd – Papers & Talks. Department of Electrical Engineering Stanford University. Google Scholar. Semantic Scholar. Papers are listed below by year of submission before they are published, or year of publication. 2024. Time dilated Bundt cake analysis of PV output. G. Ogut, B. Meyers, A. Dufour, and S. Boyd.

   • Dynamic Network Energy Management Via Proximal Message Passing

     Foundations and Trends in Optimization, 1(2):70-122, January...

   • Optimal Kernel Selection in Kernel Fisher Discriminant Analysis

     Proceedings of the 23rd International Conference on Machine...

   • Synthesizing Stability Regions for Systems With Saturating Actuators

     Proceedings IEEE Conference on Decision and Control,...

   • Robust Fisher Discriminant Analysis

     Advances in Neural Information Processing Systems 18,...

   • Computing Bounds for The Structured Singular Value Via an Interior Point Algorithm

     Proceedings of the American Control Conference, 4:2195-2196,...

   • Optimal Current Waveforms for Brushless Permanent Magnet Motors

     International Journal of Control, 88(7):1389-1399, 2015.....

   • Analytical Foundations of Volterra Series

     IMA Journal of Mathematical Control and Information, Oxford...

   • Iterative Water-Filling for Gaussian Vector Multiple Access Channels

     IEEE Transactions on Information Theory, 50(1):145-151,...

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3. web.stanford.edu › ~boyd › papersIncremental Proximal Multi-Forecast Model Predictive Control

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   13. Mai 2024 · Multi-forecast model predictive control (MF-MPC) is a control policy that creates a plan of actions over a horizon for each of a given set of forecasted scenarios or contingencies, with the constraint that the first action in all plans be the same.

4. web.stanford.edu › ~boyd › papersPV Fleet Modeling via Smooth Periodic Gaussian Copula - Stanford...

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   Vor 6 Tagen · PV Fleet Modeling via Smooth Periodic Gaussian Copula. Mehmet G. Ogut, Bennet Meyers, and Stephen P. Boyd. IEEE 50th Photovoltaic Specialists Conference (PVSC), May 2023. Final version. code. We present a method for jointly modeling power generation from a fleet of photovoltaic (PV) systems.

5. www-leland.stanford.edu › ~boyd › papersProximal Algorithms - Stanford University

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   13. Mai 2024 · Much like Newton's method is a standard tool for solving unconstrained smooth optimization problems of modest size, proximal algorithms can be viewed as an analogous tool for nonsmooth, constrained, large-scale, or distributed versions of these problems.

6. www-leland.stanford.edu › ~boyd › papersThe Science of Better: Embedded Optimization in Smart Systems

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   13. Mai 2024 · S. Boyd. Lytle Lectures Series, University of Washington, 2013. UW link. Video. Many current products and systems employ sophisticated mathematical algorithms to automatically make complex decisions, or take action, in real-time.

7. www-leland.stanford.edu › ~boyd › papersStrategic Asset Allocaiton with Illiquid Alternatives - Stanford...

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   13. Mai 2024 · Strategic Asset Allocaiton with Illiquid Alternatives. E. Luxenberg, S. Boyd, M. Kochenderfer, M. Van Beek, W. Cao, S. Diamond, A. Ulitsky, K. Menda, and V. Vairamurthy. Manuscript, July 2022. Shorter version appeared in Proceedings of the 3rd ACM International Conference on AI in Finance, p249–256, November 2022. Manuscript. ICAIF version.

8. web.stanford.edu › ~boyd › papersDistributed Optimization and Statistical Learning via the...

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   Vor 6 Tagen · After briefly surveying the theory and history of the algorithm, we discuss applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others.