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Publication search results
found 38 matches
- 2024
- Eli Amzallag, Louis-Pierre Arguin, Emma Bailey, K. Hui, R. Rao:
Evidence of Random Matrix Corrections for the Large Deviations of Selberg's Central Limit Theorem. Exp. Math. 33(1): 123-135 (2024) - 2023
- Stefan Güttel, Marcel Schweitzer:
Randomized Sketching for Krylov Approximations of Large-Scale Matrix Functions. SIAM J. Matrix Anal. Appl. 44(3): 1073-1095 (2023) - 2022
- Karl K. Sabelfeld:
Randomized Monte Carlo algorithms for matrix iterations and solving large systems of linear equations. Monte Carlo Methods Appl. 28(2): 125-133 (2022) - Yu-Qi Niu, Bing Zheng:
On global randomized block Kaczmarz algorithm for solving large-scale matrix equations. CoRR abs/2204.13920 (2022) - Stefan Güttel, Marcel Schweitzer:
Randomized sketching for Krylov approximations of large-scale matrix functions. CoRR abs/2208.11447 (2022) - 2021
- Desmond J. Higham, Nicholas J. Higham, Srikara Pranesh:
Random Matrices Generating Large Growth in LU Factorization with Pivoting. SIAM J. Matrix Anal. Appl. 42(1): 185-201 (2021) - Zenan Ling, Robert C. Qiu, Xing He, Lei Chu:
A New Approach of Exploiting Self-Adjoint Matrix Polynomials of Large Random Matrices for Anomaly Detection and Fault Location. IEEE Trans. Big Data 7(3): 548-558 (2021) - 2020
- Marco Bertola, Ayman Assra:
Random Matrix Approach for the Capacity of Large-Scale MIMO Systems using the Harish-Chandra Formula. ICSPCS 2020: 1-8 - Philippe Loubaton, Alexis Rosuel:
Large random matrix approach for testing independence of a large number of Gaussian time series. CoRR abs/2007.08806 (2020) - 2019
- Romain Couillet:
A Random Matrix Analysis and Optimization Framework to Large Dimensional Transfer Learning. CAMSAP 2019: 401-404 - Katsuya Ito, Akira Kinoshita, Masashi Yoshikawa:
Structural Change Point Detection Using A Large Random Matrix and Sparse Modeling. EDBT/ICDT Workshops 2019 - Malik Tiomoko, Romain Couillet, Florent Bouchard, Guillaume Ginolhac:
Random Matrix Improved Covariance Estimation for a Large Class of Metrics. ICML 2019: 6254-6263 - Malik Tiomoko, Florent Bouchard, Guillaume Ginolhac, Romain Couillet:
Random Matrix Improved Covariance Estimation for a Large Class of Metrics. CoRR abs/1902.02554 (2019) - 2018
- Pallaviram Sure, Narendra Babu Chindanur, Chandra Mohan Bhuma:
Large random matrix-based channel estimation for massive MIMO-OFDM uplink. IET Commun. 12(9): 1035-1041 (2018) - Xiaoyi Mai:
A Random Matrix Analysis and Improvement of Semi-Supervised Learning for Large Dimensional Data. J. Mach. Learn. Res. 19: 79:1-79:27 (2018) - Kim Batselier, Wenjian Yu, Luca Daniel, Ngai Wong:
Computing Low-Rank Approximations of Large-Scale Matrices with the Tensor Network Randomized SVD. SIAM J. Matrix Anal. Appl. 39(3): 1221-1244 (2018) - Hafiz Tiomoko Ali, Abla Kammoun, Romain Couillet:
Random Matrix-Improved Kernels For Large Dimensional Spectral Clustering. SSP 2018: 453-457 - 2017
- Xiaoyi Mai, Romain Couillet:
A random matrix analysis and improvement of semi-supervised learning for large dimensional data. CoRR abs/1711.03404 (2017) - 2016
- Ata Kabán, Jakramate Bootkrajang, Robert J. Durrant:
Toward Large-Scale Continuous EDA: A Random Matrix Theory Perspective. Evol. Comput. 24(2): 255-291 (2016) - Xiao Liu, Jianlin Xia, Maarten V. de Hoop:
Parallel Randomized and Matrix-Free Direct Solvers for Large Structured Dense Linear Systems. SIAM J. Sci. Comput. 38(5) (2016) - Hong Jiang, Yiwei Lu, Shunyou Yao:
Random matrix based method for joint DOD and DOA estimation for large scale MIMO radar in non-Gaussian noise. ICASSP 2016: 3031-3035 - Duy Khuong Nguyen, Tu Bao Ho:
Fast Parallel Randomized Algorithm for Nonnegative Matrix Factorization with KL Divergence for Large Sparse Datasets. CoRR abs/1604.04026 (2016) - 2015
- Mu Li, Wei Bi, James T. Kwok, Bao-Liang Lu:
Large-Scale Nyström Kernel Matrix Approximation Using Randomized SVD. IEEE Trans. Neural Networks Learn. Syst. 26(1): 152-164 (2015) - Aribido Joseph, Terry N. Guo, Robert C. Qiu:
Visualization of large wireless network behavior using random matrix theory. WCNC 2015: 2097-2102 - 2014
- Idan Oren, Uzy Smilansky:
Periodic Walks on Large Regular Graphs and Random Matrix Theory. Exp. Math. 23(4): 492-498 (2014) - 2013
- Michel Baes, Michael Bürgisser, Arkadi Nemirovski:
A Randomized Mirror-Prox Method for Solving Structured Large-Scale Matrix Saddle-Point Problems. SIAM J. Optim. 23(2): 934-962 (2013) - Ata Kabán, Jakramate Bootkrajang, Robert John Durrant:
Towards large scale continuous EDA: a random matrix theory perspective. GECCO 2013: 383-390 - 2012
- Florian Dupuy, Philippe Loubaton:
Optimization of MIMO Systems Capacity Using Large Random Matrix Methods. Entropy 14(11): 2122-2142 (2012) - Ismail An, Umut Simsekli, Ali Taylan Cemgil, Lale Akarun:
Large scale polyphonic music transcription using randomized matrix decompositions. EUSIPCO 2012: 2020-2024 - 2010
- Pedro Casas, Sandrine Vaton:
On the use of random neural networks for traffic matrix estimation in large-scale IP networks. IWCMC 2010: 326-330
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