免费中文无码在线播放_欧美精品18VIDEOSEX性欧美_色婷婷精品大全在线视频_精品无人区无码乱码毛片国产_大桥未久亚洲一区二区_丰满少妇三级电影_国产在线精品一区二区在线看_国产丰满乱子伦无码专区_国产精品99久久99久久久不卡

學術(shù)交流
學術(shù)交流
首頁  >  學術(shù)科研  >  學術(shù)交流  >  正文

    【學術(shù)講座】Boosting methods for interval censored data with regression and classification

    2025-07-16  點擊:[]

    講座題目Boosting methods for interval censored data with regression and classification

    講座時間:2025年7月21日(周一)10:50-11:40

    講座地點:犀浦校區(qū)3號教學樓X30425

    講座內(nèi)容簡介

    Boosting has gained significant interest across both machine learning and statistical communities. Traditional boosting algorithms, designed for fully observed random samples, often struggle with real-world problems, particularly with interval censored data. This type of data is common in survival analysis where exact event times are unobserved but fall within known intervals. Effective handling of such data is crucial in fields like medical research, reliability engineering, and social sciences. In this work, we introduce novel nonparametric boosting methods for regression and classification tasks with interval censored data. Our approaches leverage censoring unbiased transformations to adjust loss functions and impute transformed responses while maintaining model accuracy. Implemented via functional gradient descent, these methods ensure scalability and adaptability. We rigorously establish their theoretical properties. Our proposed methods not only offer a robust framework for enhancing predictive accuracy in domains where interval censored data are common but also complement existing work, expanding the applicability of existing boosting techniques. Empirical studies demonstrate robust performance across various finite-sample scenarios, highlighting the practical utility of our approaches.

    主講人簡介:Wenqing He:1986年從蘭州大學數(shù)學專業(yè)獲得學士學位,1989年從四川大學獲得應(yīng)用數(shù)學碩士學位,1996年在加拿大約克大學獲得統(tǒng)計學碩士學位,2002年從滑鐵盧大學獲得統(tǒng)計學哲學博士學位,2004年加入西安大略大學,現(xiàn)為西安大略大學統(tǒng)計與精算科學系教授、博士生導(dǎo)師。Wenqing He教授長期從事統(tǒng)計的理論和應(yīng)用的研究工作,其研究領(lǐng)域涉及生存分析,高維數(shù)據(jù)分析,統(tǒng)計學習,統(tǒng)計計算等。其研究成果發(fā)表在國際著名期刊《The Journal of the Royal Statistical Society, Series B》《Bioinformatics》《Biometrics》《Statistica Sinica》《Technometrics》《Journal of Multivariate Analysis》《Statistics in Medicine》等?,F(xiàn)為Statistics in Bioscience, Lifetime Data Analysis Journal of Statistical Distributions and Applications 等雜志副主編。他是泛華統(tǒng)計協(xié)會(ICSA)加拿大分會現(xiàn)任主席。

    上一條:【學術(shù)講座】IEEE ITSOC Distinguished Lecturer Talk: Flexible Tensor Decompositions for Learning and Optimization
    下一條:【學術(shù)講座】Two Disciplines, One Mission – A Comparative View on Making Sense of Imperfect Data from Statistical Science to Machine Learning

    關(guān)閉

沽源县| 都昌县| 太湖县| 丹阳市| 沽源县| 上饶县| 乐山市| 土默特右旗| 遂平县| 辉县市| 石狮市| 若尔盖县| 柳江县| 左云县| 永德县| 华亭县| 开远市| 息烽县| 新巴尔虎左旗| 河南省| 北票市| 文水县| 滦南县| 克什克腾旗| 菏泽市| 大安市| 明光市| 巴林左旗| 靖宇县| 长葛市| 临夏市| 涞源县| 禄丰县| 吐鲁番市| 五原县| 缙云县| 景东| 尼木县| 枣强县| 许昌县| 容城县|