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統計数学セミナー
過去の記録 ～04/26｜次回の予定｜今後の予定 04/27～
| 担当者 | 吉田朋広、荻原哲平、小池祐太 |
|---|---|
| セミナーURL | http://www.sigmath.es.osaka-u.ac.jp/~kamatani/statseminar/ |
| 目的 | 確率統計学およびその関連領域に関する研究発表, 研究紹介を行う. |
2015年11月25日(水)
14:55-18:00 数理科学研究科棟(駒場) 056号室
本講演は,数物フロンティア・リーディング大学院のFMSPレクチャーズとして行います．
Arnak Dalalyan 氏 (ENSAE ParisTech)
Learning theory and sparsity ～ Introduction into sparse recovery and compressed sensing ～
本講演は,数物フロンティア・リーディング大学院のFMSPレクチャーズとして行います．
Arnak Dalalyan 氏 (ENSAE ParisTech)
Learning theory and sparsity ～ Introduction into sparse recovery and compressed sensing ～
[ 講演概要 ]
In this introductory lecture, we will present the general framework of high-dimensional statistical modeling and its applications in machine learning and signal processing. Basic methods of sparse recovery, such as the hard and the soft thresholding, will be introduced in the context of orthonormal dictionaries and their statistical accuracy will be discussed in detail. We will also show the relation of these methods with compressed sensing and convex programming based procedures.
In this introductory lecture, we will present the general framework of high-dimensional statistical modeling and its applications in machine learning and signal processing. Basic methods of sparse recovery, such as the hard and the soft thresholding, will be introduced in the context of orthonormal dictionaries and their statistical accuracy will be discussed in detail. We will also show the relation of these methods with compressed sensing and convex programming based procedures.
