Статті в журналах з теми "Subgradient descent"
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Ознайомтеся з топ-46 статей у журналах для дослідження на тему "Subgradient descent".
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Krutikov, Vladimir, Svetlana Gutova, Elena Tovbis, Lev Kazakovtsev, and Eugene Semenkin. "Relaxation Subgradient Algorithms with Machine Learning Procedures." Mathematics 10, no. 21 (October 25, 2022): 3959. http://dx.doi.org/10.3390/math10213959.
Повний текст джерелаTovbis, Elena, Vladimir Krutikov, Predrag Stanimirović, Vladimir Meshechkin, Aleksey Popov, and Lev Kazakovtsev. "A Family of Multi-Step Subgradient Minimization Methods." Mathematics 11, no. 10 (May 11, 2023): 2264. http://dx.doi.org/10.3390/math11102264.
Повний текст джерелаLi, Gang, Minghua Li, and Yaohua Hu. "Stochastic quasi-subgradient method for stochastic quasi-convex feasibility problems." Discrete & Continuous Dynamical Systems - S 15, no. 4 (2022): 713. http://dx.doi.org/10.3934/dcdss.2021127.
Повний текст джерелаChu, Wenqing, Yao Hu, Chen Zhao, Haifeng Liu, and Deng Cai. "Atom Decomposition Based Subgradient Descent for matrix classification." Neurocomputing 205 (September 2016): 222–28. http://dx.doi.org/10.1016/j.neucom.2016.03.069.
Повний текст джерелаBedi, Amrit Singh, and Ketan Rajawat. "Network Resource Allocation via Stochastic Subgradient Descent: Convergence Rate." IEEE Transactions on Communications 66, no. 5 (May 2018): 2107–21. http://dx.doi.org/10.1109/tcomm.2018.2792430.
Повний текст джерелаNedić, Angelia, and Soomin Lee. "On Stochastic Subgradient Mirror-Descent Algorithm with Weighted Averaging." SIAM Journal on Optimization 24, no. 1 (January 2014): 84–107. http://dx.doi.org/10.1137/120894464.
Повний текст джерелаCui, Yun-Ling, Lu-Chuan Ceng, Fang-Fei Zhang, Cong-Shan Wang, Jian-Ye Li, Hui-Ying Hu, and Long He. "Modified Mann-Type Subgradient Extragradient Rules for Variational Inequalities and Common Fixed Points Implicating Countably Many Nonexpansive Operators." Mathematics 10, no. 11 (June 6, 2022): 1949. http://dx.doi.org/10.3390/math10111949.
Повний текст джерелаMontonen, O., N. Karmitsa, and M. M. Mäkelä. "Multiple subgradient descent bundle method for convex nonsmooth multiobjective optimization." Optimization 67, no. 1 (October 12, 2017): 139–58. http://dx.doi.org/10.1080/02331934.2017.1387259.
Повний текст джерелаBeck, Amir, and Marc Teboulle. "Mirror descent and nonlinear projected subgradient methods for convex optimization." Operations Research Letters 31, no. 3 (May 2003): 167–75. http://dx.doi.org/10.1016/s0167-6377(02)00231-6.
Повний текст джерелаCeng, Lu-Chuan, Li-Jun Zhu, and Tzu-Chien Yin. "Modified subgradient extragradient algorithms for systems of generalized equilibria with constraints." AIMS Mathematics 8, no. 2 (2023): 2961–94. http://dx.doi.org/10.3934/math.2023154.
Повний текст джерелаAuslender, A., and M. Teboulle. "Interior Gradient and Epsilon-Subgradient Descent Methods for Constrained Convex Minimization." Mathematics of Operations Research 29, no. 1 (February 2004): 1–26. http://dx.doi.org/10.1287/moor.1030.0062.
Повний текст джерелаCui, Yun-Ling, Lu-Chuan Ceng, Fang-Fei Zhang, Liang He, Jie Yin, Cong-Shan Wang, and Hui-Ying Hu. "Mann Hybrid Deepest-Descent Extragradient Method with Line-Search Process for Hierarchical Variational Inequalities for Countable Nonexpansive Mappings." Journal of Mathematics 2023 (May 15, 2023): 1–18. http://dx.doi.org/10.1155/2023/6177912.
Повний текст джерелаPanup, Wanida, and Rabian Wangkeeree. "Stochastic Subgradient for Large-Scale Support Vector Machine Using the Generalized Pinball Loss Function." Symmetry 13, no. 9 (September 8, 2021): 1652. http://dx.doi.org/10.3390/sym13091652.
Повний текст джерелаBoţ, Radu Ioan, and Axel Böhm. "An incremental mirror descent subgradient algorithm with random sweeping and proximal step." Optimization 68, no. 1 (June 14, 2018): 33–50. http://dx.doi.org/10.1080/02331934.2018.1482491.
Повний текст джерелаGokbayrak, Kagan, and Omer Selvi. "A Subgradient Descent Algorithm for Optimization of Initially Controllable Flow Shop Systems." Discrete Event Dynamic Systems 19, no. 2 (February 4, 2009): 267–82. http://dx.doi.org/10.1007/s10626-009-0061-z.
Повний текст джерелаArachie, Chidubem, and Bert Huang. "Adversarial Label Learning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3183–90. http://dx.doi.org/10.1609/aaai.v33i01.33013183.
Повний текст джерелаGebken, Bennet, and Sebastian Peitz. "An Efficient Descent Method for Locally Lipschitz Multiobjective Optimization Problems." Journal of Optimization Theory and Applications 188, no. 3 (January 13, 2021): 696–723. http://dx.doi.org/10.1007/s10957-020-01803-w.
Повний текст джерелаStonyakin, Fedor Sergeevich, Aleksej N. Stepanov, Alexander Vladimirovich Gasnikov, and Alexander A. Titov. "Mirror descent for constrained optimization problems with large subgradient values of functional constraints." Computer Research and Modeling 12, no. 2 (April 2020): 301–17. http://dx.doi.org/10.20537/2076-7633-2020-12-2-301-317.
Повний текст джерелаKorablev, A. I., та V. V. Eisman. "A general method of finding the direction of descent in ε-subgradient methods". Journal of Mathematical Sciences 74, № 6 (травень 1995): 1327–31. http://dx.doi.org/10.1007/bf02367719.
Повний текст джерелаRobinson, Stephen M. "Linear convergence of epsilon-subgradient descent methods for a class of convex functions." Mathematical Programming 86, no. 1 (September 1, 1999): 41–50. http://dx.doi.org/10.1007/s101070050078.
Повний текст джерелаWang, Ximing, Neng Fan, and Panos M. Pardalos. "Stochastic subgradient descent method for large-scale robust chance-constrained support vector machines." Optimization Letters 11, no. 5 (March 15, 2016): 1013–24. http://dx.doi.org/10.1007/s11590-016-1026-4.
Повний текст джерелаHand, Paul, Oscar Leong, and Vladislav Voroninski. "Optimal sample complexity of subgradient descent for amplitude flow via non-Lipschitz matrix concentration." Communications in Mathematical Sciences 19, no. 7 (2021): 2035–47. http://dx.doi.org/10.4310/cms.2021.v19.n7.a11.
Повний текст джерелаLi, Liping, Wei Xu, Tianyi Chen, Georgios B. Giannakis, and Qing Ling. "RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 1544–51. http://dx.doi.org/10.1609/aaai.v33i01.33011544.
Повний текст джерелаCeng, Lu-Chuan, Ching-Feng Wen, Yeong-Cheng Liou, and Jen-Chih Yao. "On Strengthened Inertial-Type Subgradient Extragradient Rule with Adaptive Step Sizes for Variational Inequalities and Fixed Points of Asymptotically Nonexpansive Mappings." Mathematics 10, no. 6 (March 17, 2022): 958. http://dx.doi.org/10.3390/math10060958.
Повний текст джерелаCeng, Lu-Chuan, Xiaolong Qin, Yekini Shehu, and Jen-Chih Yao. "Mildly Inertial Subgradient Extragradient Method for Variational Inequalities Involving an Asymptotically Nonexpansive and Finitely Many Nonexpansive Mappings." Mathematics 7, no. 10 (September 22, 2019): 881. http://dx.doi.org/10.3390/math7100881.
Повний текст джерелаLuo, Songting, Shingyu Leung, and Jianliang Qian. "An Adjoint State Method for Numerical Approximation of Continuous Traffic Congestion Equilibria." Communications in Computational Physics 10, no. 5 (November 2011): 1113–31. http://dx.doi.org/10.4208/cicp.020210.311210a.
Повний текст джерелаXu, Hang, Song Li, and Junhong Lin. "Low rank matrix recovery with adversarial sparse noise*." Inverse Problems 38, no. 3 (January 18, 2022): 035001. http://dx.doi.org/10.1088/1361-6420/ac44dc.
Повний текст джерелаПеревозчиков, Александр Геннадьевич, Валерий Юрьевич Решетов, and Александра Ильинична Лесик. "The ''attack-defense'' model on networks with the initial residuals of the parties." Herald of Tver State University. Series: Applied Mathematics, no. 2 (July 21, 2021): 68–81. http://dx.doi.org/10.26456/vtpmk618.
Повний текст джерелаChen, Lin, Ji-Ting Jia, Qiong Zhang, Wan-Yu Deng, and Wei Wei. "Online Sequential Projection Vector Machine with Adaptive Data Mean Update." Computational Intelligence and Neuroscience 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/5197932.
Повний текст джерелаBaillon, J. B., and R. Cominetti. "A Convergence Result for Nonautonomous Subgradient Evolution Equations and Its Application to the Steepest Descent Exponential Penalty Trajectory in Linear Programming." Journal of Functional Analysis 187, no. 2 (December 2001): 263–73. http://dx.doi.org/10.1006/jfan.2001.3828.
Повний текст джерелаПеревозчиков, Александр Геннадьевич, Валерий Юрьевич Решетов, and Александра Ильинична Лесик. "The ``attack-defense'' game with restrictions on the intake capacity of points." Herald of Tver State University. Series: Applied Mathematics, no. 3 (November 30, 2020): 78–92. http://dx.doi.org/10.26456/vtpmk600.
Повний текст джерелаXia, Zun-quan. "Finding subgradients or descent directions of convex functions by external polyhedral approximation of subdifferentials." Optimization Methods and Software 1, no. 3 (January 1992): 253–64. http://dx.doi.org/10.1080/10556789208805523.
Повний текст джерелаGriewank, Andreas, and Andrea Walther. "Polyhedral DC Decomposition and DCA Optimization of Piecewise Linear Functions." Algorithms 13, no. 7 (July 11, 2020): 166. http://dx.doi.org/10.3390/a13070166.
Повний текст джерелаDick, Josef, Guoyin Li, and Dinh Duy Tran. "A new regularization for sparse optimization." ANZIAM Journal 62 (February 7, 2022): C176—C191. http://dx.doi.org/10.21914/anziamj.v62.16076.
Повний текст джерелаGu, Bin, Yingying Shan, Xin Quan, and Guansheng Zheng. "Accelerating Sequential Minimal Optimization via Stochastic Subgradient Descent." IEEE Transactions on Cybernetics, 2019, 1–9. http://dx.doi.org/10.1109/tcyb.2019.2893289.
Повний текст джерелаSchechtman, S. "Stochastic proximal subgradient descent oscillates in the vicinity of its accumulation set." Optimization Letters, May 6, 2022. http://dx.doi.org/10.1007/s11590-022-01884-8.
Повний текст джерелаKrygin, V., and R. Khomenko. "Self-Driven Algorithm for Solving Supermodular (max,+) Labeling Problems Based on Subgradient Descent*." Cybernetics and Systems Analysis, October 21, 2022. http://dx.doi.org/10.1007/s10559-022-00485-8.
Повний текст джерелаGez, Tamir L. S., and Kobi Cohen. "Subgradient Descent Learning over Fading Multiple Access Channels with Over-the-Air Computation." IEEE Access, 2023, 1. http://dx.doi.org/10.1109/access.2023.3291023.
Повний текст джерелаCeng, Lu-Chuan, and Qing Yuan. "Composite inertial subgradient extragradient methods for variational inequalities and fixed point problems." Journal of Inequalities and Applications 2019, no. 1 (October 26, 2019). http://dx.doi.org/10.1186/s13660-019-2229-x.
Повний текст джерелаBoţ, Radu Ioan, Minh N. Dao, and Guoyin Li. "Extrapolated Proximal Subgradient Algorithms for Nonconvex and Nonsmooth Fractional Programs." Mathematics of Operations Research, December 7, 2021. http://dx.doi.org/10.1287/moor.2021.1214.
Повний текст джерелаChen, Jia, and Ioannis D. Schizas. "Multimodal correlations-based data clustering." Foundations of Data Science, 2022, 0. http://dx.doi.org/10.3934/fods.2022011.
Повний текст джерелаLatz, Jonas. "Gradient flows and randomised thresholding: sparse inversion and classification." Inverse Problems, October 19, 2022. http://dx.doi.org/10.1088/1361-6420/ac9b84.
Повний текст джерелаJianhong, Wang, and Ricardo A. Ramirez-Mendoza. "Synthesis cascade estimation for aircraft system identification." Aircraft Engineering and Aerospace Technology, June 13, 2022. http://dx.doi.org/10.1108/aeat-03-2022-0093.
Повний текст джерелаDutta, Haimonti. "A Consensus Algorithm for Linear Support Vector Machines." Management Science, August 30, 2021. http://dx.doi.org/10.1287/mnsc.2021.4042.
Повний текст джерелаWen, Jiajun, Wai Keung Wong, Xiao-Li Hu, Honglin Chu, and Zhihui Lai. "Restricted subgradient descend method for sparse signal learning." International Journal of Machine Learning and Cybernetics, April 26, 2022. http://dx.doi.org/10.1007/s13042-022-01551-5.
Повний текст джерелаWen, Jiajun, Wai Keung Wong, Xiao-Li Hu, Honglin Chu, and Zhihui Lai. "Restricted subgradient descend method for sparse signal learning." International Journal of Machine Learning and Cybernetics, April 26, 2022. http://dx.doi.org/10.1007/s13042-022-01551-5.
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