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Статті в журналах з теми "Alternating direction methods of multipliers"
Suzuki, Taiji. "STOCHASTIC ALTERNATING DIRECTION METHOD OF MULTIPLIERS FOR STRUCTURED REGULARIZATION." Journal of the Japanese Society of Computational Statistics 28, no. 1 (2015): 105–24. http://dx.doi.org/10.5183/jjscs.1502004_218.
Повний текст джерелаHager, William W., and Hongchao Zhang. "Inexact alternating direction methods of multipliers for separable convex optimization." Computational Optimization and Applications 73, no. 1 (February 7, 2019): 201–35. http://dx.doi.org/10.1007/s10589-019-00072-2.
Повний текст джерелаMa, Shiqian, Lingzhou Xue, and Hui Zou. "Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection." Neural Computation 25, no. 8 (August 2013): 2172–98. http://dx.doi.org/10.1162/neco_a_00379.
Повний текст джерелаYu, Siting, Jingjing Peng, Zengao Tang, and Zhenyun Peng. "Iterative methods to solve the constrained Sylvester equation." AIMS Mathematics 8, no. 9 (2023): 21531–53. http://dx.doi.org/10.3934/math.20231097.
Повний текст джерелаLi, Min, Li-Zhi Liao, and Xiaoming Yuan. "Inexact Alternating Direction Methods of Multipliers with Logarithmic–Quadratic Proximal Regularization." Journal of Optimization Theory and Applications 159, no. 2 (May 25, 2013): 412–36. http://dx.doi.org/10.1007/s10957-013-0334-4.
Повний текст джерелаHuang, Chunlin, and Dongbo Bu. "Predicting human contacts through alternating direction method of multipliers." International Journal of Modern Physics C 30, no. 07 (July 2019): 1940014. http://dx.doi.org/10.1142/s012918311940014x.
Повний текст джерелаAbeynanda, Hansi K., and G. H. J. Lanel. "A Study on Distributed Optimization over Large-Scale Networked Systems." Journal of Mathematics 2021 (April 29, 2021): 1–19. http://dx.doi.org/10.1155/2021/5540262.
Повний текст джерелаChao, Miantao, Caozong Cheng, and Haibin Zhang. "A Linearized Alternating Direction Method of Multipliers with Substitution Procedure." Asia-Pacific Journal of Operational Research 32, no. 03 (June 2015): 1550011. http://dx.doi.org/10.1142/s0217595915500116.
Повний текст джерелаWang, Si, Ting-Zhu Huang, Xi-le Zhao, and Jun Liu. "An Alternating Direction Method for Mixed Gaussian Plus Impulse Noise Removal." Abstract and Applied Analysis 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/850360.
Повний текст джерелаLiu, Yang, and Yazheng Dang. "Convergence Analysis of Multiblock Inertial ADMM for Nonconvex Consensus Problem." Journal of Mathematics 2023 (March 28, 2023): 1–12. http://dx.doi.org/10.1155/2023/4316267.
Повний текст джерелаДисертації з теми "Alternating direction methods of multipliers"
Selvatici, Elena. "Variational formulation for Granular Contact Dynamics simulation via the Alternating Direction Method of Multipliers." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
Знайти повний текст джерелаGu, Yan. "STUDIES ON ALTERNATING DIRECTION METHOD OF MULTIPLIERS WITH ADAPTIVE PROXIMAL TERMS FOR CONVEX OPTIMIZATION PROBLEMS." Kyoto University, 2020. http://hdl.handle.net/2433/259758.
Повний текст джерелаFécamp, Vivien. "Recalage/Fusion d'images multimodales à l'aide de graphes d'ordres supérieurs." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLC005/document.
Повний текст джерелаThe main objective of this thesis is the exploration of higher order Markov Random Fields for image registration, specifically to encode the knowledge of global transformations, like rigid transformations, into the graph structure. Our main framework applies to 2D-2D or 3D-3D registration and use a hierarchical grid-based Markov Random Field model where the hidden variables are the displacements vectors of the control points of the grid.We first present the construction of a graph that allows to perform linear registration, which means here that we can perform affine registration, rigid registration, or similarity registration with the same graph while changing only one potential. Our framework is thus modular regarding the sought transformation and the metric used. Inference is performed with Dual Decomposition, which allows to handle the higher order hyperedges and which ensures the global optimum of the function is reached if we have an agreement among the slaves. A similar structure is also used to perform 2D-3D registration.Second, we fuse our former graph with another structure able to perform deformable registration. The resulting graph is more complex and another optimisation algorithm, called Alternating Direction Method of Multipliers is needed to obtain a better solution within reasonable time. It is an improvement of Dual Decomposition which speeds up the convergence. This framework is able to solve simultaneously both linear and deformable registration which allows to remove a potential bias created by the standard approach of consecutive registrations
Tang, Shuhan. "Spectral Analysis Using Multitaper Whittle Methods with a Lasso Penalty." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1586863604571678.
Повний текст джерелаAl, Sarray Basad. "Estimation et choix de modèle pour les séries temporelles par optimisation convexe." Besançon, 2016. http://www.theses.fr/2016BESA2084.
Повний текст джерела[…] this study presents some of machine learning and convex methodes for ARMA model selection and estimation based on the conversion between ARMA –AR models and ARMA-State Space Models. Also in this study, for a time series decomposition and time series components analysis some of convex methods are implemented and simulated. The results show the ability of convex methods of analysing and modelling a given series
Ojha, Abhi. "Coupled Natural Gas and Electric Power Systems." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78666.
Повний текст джерелаMaster of Science
Velay, Maxime. "Méthodes d’optimisation distribuée pour l’exploitation sécurisée des réseaux électriques interconnectés." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT063/document.
Повний текст джерелаOur societies are more dependent on electricity than ever, thus any disturbance in the power transmission and delivery has major economic and social impact. The reliability and security of power systems are then crucial to keep, for power system operators, in addition to minimizing the system operating cost. Moreover, transmission systems are interconnected to decrease the cost of operation and improve the system security. One of the main challenges for transmission system operators is therefore to coordinate with interconnected power systems, which raises scalability, interoperability and privacy issues. Hence, this thesis is concerned with how TSOs can operate their networks in a decentralized way but coordinating their operation with other neighboring TSOs to find a cost-effective scheduling that is globally secure.The main focus of this thesis is the security of power systems, this is why the evolution of the main characteristics of the blackouts that are failures in power system security, of the period 2005-2016 is studied. The approach consists in determining what the major characteristics of the incidents of the past 10 years are, to identify what should be taken into account to mitigate the risk of incidents. The evolution have been studied and compared with the characteristics of the blackouts before 2005. The study focuses on the pre-conditions that led to those blackouts and on the cascades, and especially the role of the cascade speed. Some important features are extracted and later integrated in our work.An algorithm that solve the preventive Security Constrained Optimal Power Flow (SCOPF) problem in a fully distributed manner, is thus developed. The preventive SCOPF problem consists in adding constraints that ensure that, after the loss of any major device of the system, the new steady-state reached, as a result of the primary frequency control, does not violate any constraint. The developed algorithm uses a fine-grained decomposition and is implemented under the multi-agent system paradigm based on two categories of agents: devices and buses. The agents are coordinated with the Alternating Direction method of multipliers in conjunction with a consensus problem. This decomposition provides the autonomy and privacy to the different actors of the system and the fine-grained decomposition allows to take the most of the decomposition and provides a good scalability regarding the size of the problem. This algorithm also have the advantage of being robust to any disturbance of the system, including the separation of the system into regions.Then, to account for the uncertainty of production brought by wind farms forecast error, a two-step distributed approach is developed to solve the Chance-Constrained Optimal Power Flow problem, in a fully distributed manner. The wind farms forecast errors are modeled by independent Gaussian distributions and the mismatches with the initials are assumed to be compensated by the primary frequency response of generators. The first step of this algorithm aims at determining the sensitivity factors of the system, needed to formulate the problem. The results of this first step are inputs of the second step that is the CCOPF. An extension of this formulation provides more flexibility to the problem and consists in including the possibility to curtail the wind farms. This algorithm relies on the same fine-grained decomposition where the agents are again coordinated by the ADMM and a consensus problem. In conclusion, this two-step algorithm ensures the privacy and autonomy of the different system actors and it is de facto parallel and adapted to high performance platforms
Guiducci, Martina. "Metodo delle Direzioni Alternate per la ricostruzione di immagini Poissoniane." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19501/.
Повний текст джерелаRecupero, Giuseppe Antonio. "Un modello variazionale non convesso per il denoising di superfici." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23210/.
Повний текст джерелаScrivanti, Gabriele Luca Giovanni. "Nonsmooth Nonconvex Variational Reconstruction for Electrical Impedance Tomography." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20700/.
Повний текст джерелаКниги з теми "Alternating direction methods of multipliers"
Lin, Zhouchen, Huan Li, and Cong Fang. Alternating Direction Method of Multipliers for Machine Learning. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8.
Повний текст джерелаUnited States. National Aeronautics and Space Administration., ed. Multi-partitioning for ADI-schemes on message passing architectures. San Jose, CA: MCAT Institute, 1994.
Знайти повний текст джерелаUnited States. National Aeronautics and Space Administration., ed. Multi-partitioning for ADI-schemes on message passing architectures. San Jose, CA: MCAT Institute, 1994.
Знайти повний текст джерелаUnited States. National Aeronautics and Space Administration., ed. Multi-partitioning for ADI-schemes on message passing architectures. San Jose, CA: MCAT Institute, 1994.
Знайти повний текст джерелаBaysal, Oktay. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Norfolk, Va: Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.
Знайти повний текст джерелаUnited States. National Aeronautics and Space Administration., ed. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Norfolk, Va: Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.
Знайти повний текст джерелаUnited States. National Aeronautics and Space Administration., ed. Efficient gradient-based shape optimization methodology using inviscid/viscous CFD: Summary of research report for the period of March 9, 1995 to March 8, 1997, grant# NCC-1-211. Norfolk, Va: Dept. of Aerospace Engineering, College of Engineering and Technology, Old Dominion University, 1997.
Знайти повний текст джерелаD, Salas M., and Langley Research Center, eds. Three-dimensional simulation of vortex breakdown. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.
Знайти повний текст джерелаD, Salas M., and Langley Research Center, eds. Three-dimensional simulation of vortex breakdown. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.
Знайти повний текст джерелаKuruvila, G. Three-dimensional simulation of vortex breakdown. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.
Знайти повний текст джерелаЧастини книг з теми "Alternating direction methods of multipliers"
Glowinski, Roland. "On Alternating Direction Methods of Multipliers: A Historical Perspective." In Computational Methods in Applied Sciences, 59–82. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9054-3_4.
Повний текст джерелаYan, Ming, and Wotao Yin. "Self Equivalence of the Alternating Direction Method of Multipliers." In Splitting Methods in Communication, Imaging, Science, and Engineering, 165–94. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41589-5_5.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "Derivations of ADMM." In Alternating Direction Method of Multipliers for Machine Learning, 11–23. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_2.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "ADMM for Nonconvex Optimization." In Alternating Direction Method of Multipliers for Machine Learning, 113–41. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_4.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "ADMM for Distributed Optimization." In Alternating Direction Method of Multipliers for Machine Learning, 207–40. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_6.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "ADMM for Deterministic and Convex Optimization." In Alternating Direction Method of Multipliers for Machine Learning, 25–111. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_3.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "Introduction." In Alternating Direction Method of Multipliers for Machine Learning, 1–9. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_1.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "Practical Issues and Conclusions." In Alternating Direction Method of Multipliers for Machine Learning, 241–47. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_7.
Повний текст джерелаLin, Zhouchen, Huan Li, and Cong Fang. "Stochastic ADMM." In Alternating Direction Method of Multipliers for Machine Learning, 143–205. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9840-8_5.
Повний текст джерелаKhakhutskyy, Valeriy, and Dirk Pflüger. "Alternating Direction Method of Multipliers for Hierarchical Basis Approximators." In Lecture Notes in Computational Science and Engineering, 221–38. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04537-5_9.
Повний текст джерелаТези доповідей конференцій з теми "Alternating direction methods of multipliers"
Kadkhodaie, Mojtaba, Konstantina Christakopoulou, Maziar Sanjabi, and Arindam Banerjee. "Accelerated Alternating Direction Method of Multipliers." In KDD '15: The 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2783258.2783400.
Повний текст джерелаRoutray, Chinmay, and Soumya Ranjan Sahoo. "Emulation Alternating Direction Method of Multipliers." In 2022 Eighth Indian Control Conference (ICC). IEEE, 2022. http://dx.doi.org/10.1109/icc56513.2022.10093531.
Повний текст джерелаZhang, Guoqiang, and Richard Heusdens. "Bi-alternating direction method of multipliers." In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6638272.
Повний текст джерелаWei, Ermin, and Asuman Ozdaglar. "Distributed Alternating Direction Method of Multipliers." In 2012 IEEE 51st Annual Conference on Decision and Control (CDC). IEEE, 2012. http://dx.doi.org/10.1109/cdc.2012.6425904.
Повний текст джерелаLing, Qing, and Alejandro Ribeiro. "Decentralized linearized alternating direction method of multipliers." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6854644.
Повний текст джерелаRoutray, Chinmay, and Soumya Ranjan Sahoo. "Decentralizing Consensus-Alternating Direction Method of Multipliers." In 2023 European Control Conference (ECC). IEEE, 2023. http://dx.doi.org/10.23919/ecc57647.2023.10178331.
Повний текст джерелаMokhtari, Aryan, Wei Shi, Qing Ling, and Alejandro Ribeiro. "Decentralized quadratically approximated alternating direction method of multipliers." In 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2015. http://dx.doi.org/10.1109/globalsip.2015.7418306.
Повний текст джерелаMakhdoumi, Ali, and Asuman Ozdaglar. "Broadcast-based distributed alternating direction method of multipliers." In 2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2014. http://dx.doi.org/10.1109/allerton.2014.7028466.
Повний текст джерелаZhang, Guoqiang, and Richard Heusdens. "Bi-alternating direction method of multipliers over graphs." In ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2015. http://dx.doi.org/10.1109/icassp.2015.7178636.
Повний текст джерелаCerone, V., S. M. Fosson, S. Pirrera, and D. Regruto. "Alternating direction method of multipliers for polynomial optimization." In 2023 European Control Conference (ECC). IEEE, 2023. http://dx.doi.org/10.23919/ecc57647.2023.10178190.
Повний текст джерелаЗвіти організацій з теми "Alternating direction methods of multipliers"
Ouyang, Yuyuan, Yumei Chen, Guanghui Lan, Jr Pasiliao, and Eduardo. An Accelerated Linearized Alternating Direction Method of Multipliers. Fort Belvoir, VA: Defense Technical Information Center, February 2014. http://dx.doi.org/10.21236/ada595588.
Повний текст джерелаYan, Ming, and Wotao Yin. Self Equivalence of the Alternating Direction Method of Multipliers. Fort Belvoir, VA: Defense Technical Information Center, August 2014. http://dx.doi.org/10.21236/ada610274.
Повний текст джерелаDeng, Wei, and Wotao Yin. On the Global and Linear Convergence of the Generalized Alternating Direction Method of Multipliers. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada567407.
Повний текст джерелаJohnsson, S. L., Youcef Saad, and Martin H. Schultz. Alternating Direction Methods on Multiprocessors. Fort Belvoir, VA: Defense Technical Information Center, October 1985. http://dx.doi.org/10.21236/ada161973.
Повний текст джерелаLambert, Michael Allen. Field simulation of axisymmetric plasma screw pinches by alternating-direction-implicit methods. Office of Scientific and Technical Information (OSTI), June 1996. http://dx.doi.org/10.2172/410408.
Повний текст джерела