应pc加拿大预测准确率李周平副教授邀请，武汉大学pc加拿大预测准确率刘妍岩教授将于2017年10月13日至15日访问我校并作学术报告。
报告题目：A Constructive Approach to High-Dimensional Linear Regression
时 间：10月14日（星期六）下午3:00
地 点：齐云楼911报告厅.
摘 要：We develop a constructive approach to estimate sparse and approximately sparse linear regression models in high-dimensions. The proposed approach is a computational algorithm that generates a sequence of solutions iteratively, based on support detection using primal and dual information and root finding according to a modified KKT condition for the L_0-penalized least squares criterion. We refer to the proposed algorithm as SDAR for brevity. Under certain different regularity conditions on the design matrix and sparsity assumption on the regression coefficients, we show that with high probability, the estimation errors decay exponentially to the minimax error bound and to the optimal error bound in more than O(\sqrt{K}log(R)) and O(log(R)) steps respectively, where K is the sparsity level, R is the relative magnitude of the nonzero target coefficients. Computational complexity analysis shows that the cost of SDAR is O(np) in each step. Moreover the oracle estimator can be exactly recovered with high probability at the same cost if we know K. We also consider ASDAR, an adaptive version of SDAR to make it more practical in applications. Numerical comparisons with Lasso and MCP and greedy methods indicate that ASDAR is competitive with or outperforms them both in accuracy and efficiency.
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刘妍岩教授简介
刘妍岩教授现任武汉大学pc加拿大预测准确率教授（博士生导师），于2001年获得武汉大学理学博士学位。主要研究方向为生存分析、半参数统计推断、高维数据统计分析等。主持完成国家自然科学基金面上项目2项、青年基金项目1项，正在主持国家自然科学基金面上项目1项，参加完成的项目“风险模型中的统计方法及相关理论与应用”获2013年湖北省自然科学奖三等奖（排名第一）。在相关研究领域发表SCI研究论文40余篇。目前担任中国现场统计学会第九届理事会理事、中国教育统计协会常务理事、中国数学会女数学家及西部数学发展工作委员会委员。
应用数学与复杂系统重点实验室
pc加拿大预测准确率
大数据科学研究中心
萃英学院
二〇一七年十月十日
