報告題目：Accelerated greedy randomized augmented Kaczmarz algorithm for inconsistent linear systems
報告專家：劉永博士，常熟理工學院
報告地點：騰訊會議(會議號328-171-9712;密碼314159)
報告時間：2024年1月4日晚7:30-9:30
報告摘要：For solving inconsistent linear systems of equations iteratively, we further generalize the greedy randomized augmented Kaczmarz (GRAK) algorithm by introducing a nonzero parameter in the involved augmented linear system of the above inconsistent linear system, obtaining a class of accelerated greedy randomized augmented Kaczmarz algorithms.These algorithms involve one iteration parameter whose special choice can recover the GRAK algorithm, as well as yield new ones. Theoretical analyses show that the new algorithms converge to the unique solution of the augmented linear system. Moreover, the optimal choice of the parameter involved and the corresponding convergence rates of the new algorithms are computed exactly. Numerical results show that our algorithms can be much more effective than the GRAK algorithm in terms of both iteration counts and computing times.
報告人簡介：劉永博士，常熟理工學院數學與統計學院講師，2020年畢業于上海大學計算數學專業，主要研究方向為隨機數值代數，現主持江蘇省高等學校面上項目一項，發表論文10余篇
作者：吳念慈；編輯：劉鹍；審核：郭暉；發布：郭敏
