Random matrix methods for wireless communications

von Couillet, Romain
Veröffentlicht 2011

REVISITING THE BETHE-HESSIAN: IMPROVED COMMUNITY DETECTION IN SPARSE HETEROGENEOUS GRAPHS

von Dall'Amico, Lorenzo
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 6 of 20 (2020)

COMMUNITY DETECTION IN SPARSE TIME-EVOLVING GRAPHS WITH A DYNAMICAL BETHE-HESSIAN

von Amico, Lorenzo Dall'
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 10 of 27 (2021)

A RANDOM MATRIX ANALYSIS OF RANDOM FOURIER FEATURES: BEYOND THE GAUSSIAN KERNEL, A PRECISE PHASE TRANSITION, AND THE CORRESPONDING DOUBLE DESCENT

von Liao, Zhenyu
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 17 of 27 (2021)

TWO-WAY KERNEL MATRIX PUNCTURING: TOWARDS RESOURCE-EFFICIENT PCA AND SPECTRAL CLUSTERING

von COUILLET, ROMAIN
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 3 of 16 (2022)

RANDOM MATRIX THEORY PROVES THAT DEEP LEARNING REPRESENTATIONS OF GAN-DATA BEILAVE AS GAUSSIAN MIXTURES

von Seddik, Mohamed El Amine
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 11 of 15 (2021)