Journal articles on the topic 'Approximate norm descent methods'
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Morini, Benedetta, Margherita Porcelli, and Philippe L. Toint. "Approximate norm descent methods for constrained nonlinear systems." Mathematics of Computation 87, no. 311 (May 11, 2017): 1327–51. http://dx.doi.org/10.1090/mcom/3251.
Full textJin, Yang, Li, and Liu. "Sparse Recovery Algorithm for Compressed Sensing Using Smoothed l0 Norm and Randomized Coordinate Descent." Mathematics 7, no. 9 (September 9, 2019): 834. http://dx.doi.org/10.3390/math7090834.
Full textXu, Kai, and Zhi Xiong. "Nonparametric Tensor Completion Based on Gradient Descent and Nonconvex Penalty." Symmetry 11, no. 12 (December 12, 2019): 1512. http://dx.doi.org/10.3390/sym11121512.
Full textKo, Dongnam, and Enrique Zuazua. "Model predictive control with random batch methods for a guiding problem." Mathematical Models and Methods in Applied Sciences 31, no. 08 (July 2021): 1569–92. http://dx.doi.org/10.1142/s0218202521500329.
Full textUtomo, Rukmono Budi. "METODE NUMERIK STEPEST DESCENT DENGAN DIRECTION DAN NORMRERATA ARITMATIKA." AKSIOMA Journal of Mathematics Education 5, no. 2 (January 3, 2017): 128. http://dx.doi.org/10.24127/ajpm.v5i2.673.
Full textGoh, B. S. "Approximate Greatest Descent Methods for Optimization with Equality Constraints." Journal of Optimization Theory and Applications 148, no. 3 (November 16, 2010): 505–27. http://dx.doi.org/10.1007/s10957-010-9765-3.
Full textXiao, Yunhai, Chunjie Wu, and Soon-Yi Wu. "Norm descent conjugate gradient methods for solving symmetric nonlinear equations." Journal of Global Optimization 62, no. 4 (July 11, 2014): 751–62. http://dx.doi.org/10.1007/s10898-014-0218-7.
Full textQiu, Yixuan, and Xiao Wang. "Stochastic Approximate Gradient Descent via the Langevin Algorithm." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 5428–35. http://dx.doi.org/10.1609/aaai.v34i04.5992.
Full textYang, Yin, and Yunqing Huang. "Spectral-Collocation Methods for Fractional Pantograph Delay-Integrodifferential Equations." Advances in Mathematical Physics 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/821327.
Full textPoggio, Tomaso, Andrzej Banburski, and Qianli Liao. "Theoretical issues in deep networks." Proceedings of the National Academy of Sciences 117, no. 48 (June 9, 2020): 30039–45. http://dx.doi.org/10.1073/pnas.1907369117.
Full textBoykov, Ilya, Vladimir Roudnev, and Alla Boykova. "Approximate Methods for Solving Linear and Nonlinear Hypersingular Integral Equations." Axioms 9, no. 3 (July 1, 2020): 74. http://dx.doi.org/10.3390/axioms9030074.
Full textShi, Dongyang, and Zhiyun Yu. "Low-Order Nonconforming Mixed Finite Element Methods for Stationary Incompressible Magnetohydrodynamics Equations." Journal of Applied Mathematics 2012 (2012): 1–21. http://dx.doi.org/10.1155/2012/825609.
Full textWei, Yunxia, and Yanping Chen. "Convergence Analysis of the Spectral Methods for Weakly Singular Volterra Integro-Differential Equations with Smooth Solutions." Advances in Applied Mathematics and Mechanics 4, no. 1 (February 2012): 1–20. http://dx.doi.org/10.4208/aamm.10-m1055.
Full textHENSHALL, JOHN M., and BRUCE TIER. "An algorithm for sampling descent graphs in large complex pedigrees efficiently." Genetical Research 81, no. 3 (June 2003): 205–12. http://dx.doi.org/10.1017/s0016672303006232.
Full textYang, Long, Yu Zhang, Gang Zheng, Qian Zheng, Pengfei Li, Jianhang Huang, and Gang Pan. "Policy Optimization with Stochastic Mirror Descent." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (June 28, 2022): 8823–31. http://dx.doi.org/10.1609/aaai.v36i8.20863.
Full textHe, Linjie, Yumin Chen, Caiming Zhong, and Keshou Wu. "Granular Elastic Network Regression with Stochastic Gradient Descent." Mathematics 10, no. 15 (July 27, 2022): 2628. http://dx.doi.org/10.3390/math10152628.
Full textYang, Yin, Xinfa Yang, Jindi Wang, and Jie Liu. "The numerical solution of the time-fractional non-linear Klein-Gordon equation via spectral collocation method." Thermal Science 23, no. 3 Part A (2019): 1529–37. http://dx.doi.org/10.2298/tsci180824220y.
Full textZeng, Xueying, Lixin Shen, Yuesheng Xu, and Jian Lu. "Matrix completion via minimizing an approximate rank." Analysis and Applications 17, no. 05 (September 2019): 689–713. http://dx.doi.org/10.1142/s0219530519400025.
Full textSiahlooei, Esmaeil, and Seyed Abolfazl Shahzadeh Fazeli. "Two Iterative Methods for Solving Linear Interval Systems." Applied Computational Intelligence and Soft Computing 2018 (October 8, 2018): 1–13. http://dx.doi.org/10.1155/2018/2797038.
Full textJacobsen, Andrew, Matthew Schlegel, Cameron Linke, Thomas Degris, Adam White, and Martha White. "Meta-Descent for Online, Continual Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3943–50. http://dx.doi.org/10.1609/aaai.v33i01.33013943.
Full textBonesky, Thomas, Kamil S. Kazimierski, Peter Maass, Frank Schöpfer, and Thomas Schuster. "Minimization of Tikhonov Functionals in Banach Spaces." Abstract and Applied Analysis 2008 (2008): 1–19. http://dx.doi.org/10.1155/2008/192679.
Full textSandilya, Ruchi, and Sarvesh Kumar. "Convergence Analysis of Discontinuous Finite Volume Methods for Elliptic Optimal Control Problems." International Journal of Computational Methods 13, no. 02 (March 2016): 1640012. http://dx.doi.org/10.1142/s0219876216400120.
Full textShi, Xiulian. "Spectral Collocation Methods for Fractional Integro-Differential Equations with Weakly Singular Kernels." Journal of Mathematics 2022 (October 25, 2022): 1–9. http://dx.doi.org/10.1155/2022/3767559.
Full textCarpentier, Jean, and Sebastien Blandin. "Approximate Gradient Descent Convergence Dynamics for Adaptive Control on Heterogeneous Networks." Proceedings of the International Conference on Automated Planning and Scheduling 29 (May 25, 2021): 68–76. http://dx.doi.org/10.1609/icaps.v29i1.3461.
Full textInnocenti, Luca, Leonardo Banchi, Sougato Bose, Alessandro Ferraro, and Mauro Paternostro. "Approximate supervised learning of quantum gates via ancillary qubits." International Journal of Quantum Information 16, no. 08 (December 2018): 1840004. http://dx.doi.org/10.1142/s021974991840004x.
Full textHan, Xu, Jiasong Wu, Lu Wang, Yang Chen, Lotfi Senhadji, and Huazhong Shu. "Linear Total Variation Approximate Regularized Nuclear Norm Optimization for Matrix Completion." Abstract and Applied Analysis 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/765782.
Full textBuong, Nguyen, Nguyen Anh, and Khuat Binh. "Steepest-descent Ishikawa iterative methods for a class of variational inequalities in Banach spaces." Filomat 34, no. 5 (2020): 1557–69. http://dx.doi.org/10.2298/fil2005557b.
Full textYu, Hong, Tongjun Sun, and Na Li. "The Time DiscontinuousH1-Galerkin Mixed Finite Element Method for Linear Sobolev Equations." Discrete Dynamics in Nature and Society 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/618258.
Full textKarakida, Ryo, and Kazuki Osawa. "Understanding approximate Fisher information for fast convergence of natural gradient descent in wide neural networks*." Journal of Statistical Mechanics: Theory and Experiment 2021, no. 12 (December 1, 2021): 124010. http://dx.doi.org/10.1088/1742-5468/ac3ae3.
Full textKIM, MI-YOUNG. "DISCONTINUOUS GALERKIN METHODS FOR THE LOTKA–MCKENDRICK EQUATION WITH FINITE LIFE-SPAN." Mathematical Models and Methods in Applied Sciences 16, no. 02 (February 2006): 161–76. http://dx.doi.org/10.1142/s0218202506001108.
Full textBertrand, Fleurianne, Zhiqiang Cai, and Eun Young Park. "Least-Squares Methods for Elasticity and Stokes Equations with Weakly Imposed Symmetry." Computational Methods in Applied Mathematics 19, no. 3 (July 1, 2019): 415–30. http://dx.doi.org/10.1515/cmam-2018-0255.
Full textZhu, Jun, Changwei Chen, Shoubao Su, and Zinan Chang. "Compressive Sensing of Multichannel EEG Signals via lq Norm and Schatten-p Norm Regularization." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/2189563.
Full textZhou, Jingcheng, Wei Wei, Ruizhi Zhang, and Zhiming Zheng. "Damped Newton Stochastic Gradient Descent Method for Neural Networks Training." Mathematics 9, no. 13 (June 29, 2021): 1533. http://dx.doi.org/10.3390/math9131533.
Full textZhang, Bin, Liuliu Wang, Shuang Li, Futai Xie, and Lideng Wei. "Airborne Single-Pass Multi-Baseline InSAR Layover Separation Method Based on Multi-Look Compressive Sensing." Applied Sciences 12, no. 24 (December 9, 2022): 12658. http://dx.doi.org/10.3390/app122412658.
Full textSHISHKIN, GRIGORII I., and PETR N. VABISHCHEVICH. "PARALLEL DOMAIN DECOMPOSITION METHODS WITH THE OVERLAPPING OF SUBDOMAINS FOR PARABOLIC PROBLEMS." Mathematical Models and Methods in Applied Sciences 06, no. 08 (December 1996): 1169–85. http://dx.doi.org/10.1142/s0218202596000493.
Full textYadav, Sangita, and Amiya K. Pani. "Superconvergent discontinuous Galerkin methods for nonlinear parabolic initial and boundary value problems." Journal of Numerical Mathematics 27, no. 3 (September 25, 2019): 183–202. http://dx.doi.org/10.1515/jnma-2018-0035.
Full textWang, Yi Yan, and Shi Yun Wu. "Adaptive Image Denoising Approach Based on Generalized Lp Norm Variational Model." Applied Mechanics and Materials 556-562 (May 2014): 4851–55. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.4851.
Full textCao, Yongcan, and Huixin Zhan. "Efficient Multi-objective Reinforcement Learning via Multiple-gradient Descent with Iteratively Discovered Weight-Vector Sets." Journal of Artificial Intelligence Research 70 (January 20, 2021): 319–49. http://dx.doi.org/10.1613/jair.1.12270.
Full textJurisic Bellotti, Maja, and Mladen Vucic. "Sparse FIR Filter Design Based on Signomial Programming." Elektronika ir Elektrotechnika 26, no. 1 (February 16, 2020): 40–45. http://dx.doi.org/10.5755/j01.eie.26.1.23560.
Full textFicarella, Elisa, Luciano Lamberti, and Sadik Ozgur Degertekin. "Mechanical Identification of Materials and Structures with Optical Methods and Metaheuristic Optimization." Materials 12, no. 13 (July 2, 2019): 2133. http://dx.doi.org/10.3390/ma12132133.
Full textSi, Weijian, Xinggen Qu, Yilin Jiang, and Tao Chen. "Multiple Sparse Measurement Gradient Reconstruction Algorithm for DOA Estimation in Compressed Sensing." Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/152570.
Full textXiong, Huan. "DPCD: Discrete Principal Coordinate Descent for Binary Variable Problems." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 9 (June 28, 2022): 10391–98. http://dx.doi.org/10.1609/aaai.v36i9.21281.
Full textWunderlich, Jonathan, and Michael Plum. "Computer-assisted Existence Proofs for One-dimensional Schrödinger-Poisson Systems." Acta Cybernetica 24, no. 3 (March 16, 2020): 373–91. http://dx.doi.org/10.14232/actacyb.24.3.2020.6.
Full textSun, Min, Jing Liu, and Yaru Wang. "Two Improved Conjugate Gradient Methods with Application in Compressive Sensing and Motion Control." Mathematical Problems in Engineering 2020 (May 5, 2020): 1–11. http://dx.doi.org/10.1155/2020/9175496.
Full textZuo, Ming, Shuguo Xie, Xian Zhang, and Meiling Yang. "DOA Estimation Based on Weighted l1-norm Sparse Representation for Low SNR Scenarios." Sensors 21, no. 13 (July 5, 2021): 4614. http://dx.doi.org/10.3390/s21134614.
Full textHe, Guodong, Maozhong Song, Shanshan Zhang, Huiping Qin, and Xiaojuan Xie. "GPS Sparse Multipath Signal Estimation Based on Compressive Sensing." Wireless Communications and Mobile Computing 2021 (May 11, 2021): 1–9. http://dx.doi.org/10.1155/2021/5583429.
Full textLi, Ning, Qing-Wen Wang, and Jing Jiang. "An Efficient Algorithm for the Reflexive Solution of the Quaternion Matrix EquationAXB+CXHD=F." Journal of Applied Mathematics 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/217540.
Full textSun, Zhenzhen, and Yuanlong Yu. "Robust multi-class feature selection via l2,0-norm regularization minimization." Intelligent Data Analysis 26, no. 1 (January 14, 2022): 57–73. http://dx.doi.org/10.3233/ida-205724.
Full textJain, Nishant, Brian Coyle, Elham Kashefi, and Niraj Kumar. "Graph neural network initialisation of quantum approximate optimisation." Quantum 6 (November 17, 2022): 861. http://dx.doi.org/10.22331/q-2022-11-17-861.
Full textMasegosa, Andrés R., Rafael Cabañas, Helge Langseth, Thomas D. Nielsen, and Antonio Salmerón. "Probabilistic Models with Deep Neural Networks." Entropy 23, no. 1 (January 18, 2021): 117. http://dx.doi.org/10.3390/e23010117.
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