報告時間：
8月20日：9:00—12:00 ，14:00—16:00
8月22日：9:00—12:00 ，14:00—16:00
8月23日：9:00—12:00 ，14:00—16:00
報告地點：北辰校區(qū)理學院西教五416
報告題目：Low-Rank Matrix Optimization: Theory and Algorithms
報告嘉賓： Qi Houduo教授
報告簡介：
One of the purposes in machine learning is to reveal and explore the structure among data. When data is put in arrays, they tend to be of low rank. Therefore, low-rank matrix optimization has become increasingly important in machine learning algorithms. This series of talks aims to provide a selective overview of the topic. We pay particular attention to efficient algorithms and try to elaborate on important optimization techniques that are uniquely related to low-rank optimization. The principle in guiding our selection of the material is the speed and solution quality of the resulting algorithms. After this course, one is expected to appreciate the difficulty of the problem, what works and what do not, and more importantly we are left for further exploration.
We will focus on the following (selective) aspects of the topic:
Low-rank matrix optimization: motivating examples (from Principle33 Component Analysis to Low-rank and sparse optimization, Low-rank Hankel matrix optimization for spectrally sparse optimization)
Penalty methods (the need for regularization, proximal operators, DC penalties)
Methods of Alternating Projections (global and linear convergence, and its penalized version)
A show-case example: outlier detection via low-rank EDM (Euclidean Distance Matrix) optimization.
嘉賓簡介：
Qi Houduo教授（主頁：http://www.personal.soton.ac.uk/hdqi）為英國南安普敦大學教授，博士生導師。1990年畢業(yè)于北京大學統(tǒng)計學專業(yè)，1993年獲曲阜師范大學碩士學位, 1996年中國科學研究院數(shù)學與系統(tǒng)科學研究院應用數(shù)學研究所博士畢業(yè)。曾在香港理工大學、新南威爾士大學等做博士后研究，獲澳大利亞研究委員會（ARC）資助，以及ARC和享有全球盛譽的Queen Elizabeth II Fellowship獎勵。研究方向有：約束優(yōu)化、矩陣優(yōu)化、變分不等式、數(shù)值分析等。在國際頂級期刊SIAM on Optimization, Mathematical Programming 等雜志發(fā)表高水平研究論文十余篇。
