報(bào) 告 人：胡慶培 研究員
報(bào)告題目：數(shù)據(jù)與機(jī)理結(jié)合的數(shù)據(jù)恢復(fù)與建模方法
報(bào)告時(shí)間：2023年12月7日（周四）下午14:30
報(bào)告地點(diǎn)：分析測試中心102會(huì)議室
主辦單位：數(shù)學(xué)研究院、數(shù)學(xué)與統(tǒng)計(jì)學(xué)院、科學(xué)技術(shù)研究院
報(bào)告人簡介：
胡慶培，中國科學(xué)院數(shù)學(xué)與系統(tǒng)科學(xué)研究院研究員，現(xiàn)任系統(tǒng)所統(tǒng)計(jì)室主任、質(zhì)量與數(shù)據(jù)科學(xué)中心常務(wù)副主任、航天產(chǎn)品可靠性技術(shù)與質(zhì)量科學(xué)聯(lián)合實(shí)驗(yàn)室副主任。長期從事工業(yè)統(tǒng)計(jì)與系統(tǒng)可靠性的研究工作，在系統(tǒng)可靠性綜合評(píng)估、加速退化試驗(yàn)評(píng)估與設(shè)計(jì)、系統(tǒng)可靠性增長建模與推斷、復(fù)雜數(shù)據(jù)分析等方向研究成果發(fā)表于IISE、ITR、RESS、JQT、NeurIPS等，曾獲關(guān)肇直青年科學(xué)獎(jiǎng)、IISE最佳年度論文提名獎(jiǎng)等。目前擔(dān)任系統(tǒng)科學(xué)與數(shù)學(xué)、IISE、QTQM、QREI學(xué)術(shù)期刊的副編輯或編委。
報(bào)告摘要：
Because of the widespread existence of noise and data corruption, recovering the true regression parameters with a certain proportion of corrupted response variables is an essential task. Methods to overcome this problem often involve robust least-squares regression, but few methods perform well when confronted with severeadaptive adversarial attacks. In many applications, prior knowledge is often available from historical data or engineering experience, and by incorporating prior information into a robust regression method, we develop an effective robust regression method that can resist adaptive adversarial attacks. First, we propose the novel TRIP (hard Thresholding approach to Robust regression with sImple Prior) algorithm, which improves the breakdown point when facing adaptive adversarial attacks. Then, to improve the robustness and reduce the estimation error caused by the inclusion of priors, we use the idea of Bayesian reweighting to construct the more robust BRHT (robust Bayesian Reweighting regression via Hard Thresholding) algorithm. We prove the theoretical convergence of the proposed algorithms under mild conditions, and extensive experiments show that under different types of dataset attacks, our algorithms outperform other benchmark ones. Finally, we apply our methods to a data-recovery problem in a real-world application involving a space solar array, demonstrating their good applicability.