POIGNARD Benjamin ＰＯＩＧＮＡＲＤＢＥＮＪＡＭＩＮ

… Alternative Names

Researcher Number	40845252
Other IDs
Affiliation (Current)	2022: 大阪大学, 大学院経済学研究科, 講師
Affiliation (based on the past Project Information) *help	2022: 大阪大学, 経済学研究科(研究院), 講師 2019 – 2021: 大阪大学, 経済学研究科, 講師
Review Section/Research Field	Principal Investigator 0107:Economics, business administration, and related fields / Basic Section 07030:Economic statistics-related Except Principal Investigator Basic Section 61030:Intelligent informatics-related
Keywords	Principal Investigator High dimension / M-estimation / Sparsity / High-dimension / Multivariate Time Series / Penalisation Except Principal Investigator 選択的推論 / カーネル法 / 統計的推論 / 機械学習 / 特徴選択

Sparse statistical approach for multivariate modellingPrincipal Investigator
- Principal Investigator
  
  POIGNARD BENJAMIN
- Project Period (FY)
  2022 – 2024
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 07030:Economic statistics-related
- Research Institution
  Osaka University
Research and development of nonlinear Selective Inference for high-dimensional and small number of samples data
- Principal Investigator
  
  山田誠
- Project Period (FY)
  2020 – 2023
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  Kyoto University
Parsimonious statistical modelling for high-dimensional problemsPrincipal Investigator
- Principal Investigator
  
  POIGNARD BENJAMIN
- Project Period (FY)
  2019 – 2021
- Research Category
  
  Grant-in-Aid for Research Activity Start-up
- Review Section
  
  0107:Economics, business administration, and related fields
- Research Institution
  Osaka University

All 2021 2020 2019

All Journal Article Presentation

[Journal Article] The finite sample properties of sparse M-estimators with pseudo-observations2021
- Author(s)
  Benjamin POIGNARD; Jean-David FERMANIAN
- Journal Title
  
  Annals of the Institute of Statistical Mathematics
  
  Volume: To appear
- DOI
  10.1007/s10463-021-00785-4
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Journal Article] High-dimensional penalized ARCH processes2020
- Author(s)
  Benjamin POIGNARD; Jean-David FERMANIAN
- Journal Title
  
  Econometric Reviews
  
  Volume: 40 Pages: 86-107
- DOI
  10.1080/07474938.2020.1761153
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Journal Article] Sparse Hilbert-Schmidt Independence Criterion Regression2020
- Author(s)
  Benjamin POIGNARD; Makoto YAMADA
- Journal Title
  
  Proceedings of Machine Learning Research, AISTATS 2020
  
  Volume: To appear
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Journal Article] Sparse Hilbert-Schmidt Independence Criterion Regression2020
- Author(s)
  Benjamin POIGNARD; Makoto Yamada
- Journal Title
  
  Proceedings of Machine Learning Research, AISTATS 2020
  
  Volume: 108 Pages: 538-548
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Journal Article] Statistical analysis of sparse approximate factor models2020
- Author(s)
  Poignard Benjamin、Terada Yoshikazu
- Journal Title
  
  Electronic Journal of Statistics
  
  Volume: 14 Pages: 3315-3365
- DOI
  10.1214/20-ejs1745
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K19756, KAKENHI-PROJECT-19K23193
[Presentation] Sparse Hilbert-Schmidt Independence Regression Criterion2021
- Author(s)
  Benjamin POIGNARD
- Organizer
  Riken AIP - 9th AIP Open Seminar
- Invited
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] Sparse Hilbert-Schmidt Independence Regression Criterion2020
- Author(s)
  Benjamin POIGNARD
- Organizer
  AISTATS 2020 conference
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] High-dimensional Sparse Multivariate Stochastic Volatility Models2020
- Author(s)
  Benjamin POIGNARD
- Organizer
  CFE-CMStatistics 2020 Conference
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] High-dimensional Sparse Multivariate Stochastic Volatility Models2020
- Author(s)
  Benjamin POIGNARD
- Organizer
  Seminar presentation at the 4th Asian Quantitative Finance Seminar
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] Sparse Hilbert-Schmidt Independence Regression Criterion2020
- Author(s)
  Benjamin POIGNARD
- Organizer
  Seminar presentation at the Institute of Scientific and Industrial Research of Osaka University
- Invited
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] Long term asset allocation2019
- Author(s)
  Benjamin POIGNARD
- Organizer
  Marunochi Quantitative Finance Seminar
- Invited
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] Sparse Hilbert-Schmidt Independence Criterion Regression2019
- Author(s)
  Benjamin POIGNARD
- Organizer
  MMDS Seminar, Osaka University
- Invited
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] The Finite Sample Properties of Sparse M-estimators with Pseudo-Observations2019
- Author(s)
  Benjamin POIGNARD
- Organizer
  EcoSta
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193
[Presentation] Statistical analysis of sparse approximate factor models2019
- Author(s)
  Benjamin POIGNARD
- Organizer
  SETA International Conference
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K23193

1. 山田誠 (00581323)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
2. 下平英寿 (00290867)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
3. 寺田吉壱

# of Collaborated Projects: 0 results

# of Collaborated Products: 1 results

POIGNARD Benjamin ＰＯＩＧＮＡＲＤ ＢＥＮＪＡＭＩＮ

POIGNARD BENJAMIN ポイニャル ベンジャミン

Research Projects

Research Products

Co-Researchers

Sparse statistical approach for multivariate modellingPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Research and development of nonlinear Selective Inference for high-dimensional and small number of samples data

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Parsimonious statistical modelling for high-dimensional problemsPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] The finite sample properties of sparse M-estimators with pseudo-observations2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] High-dimensional penalized ARCH processes2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Sparse Hilbert-Schmidt Independence Criterion Regression2020

Author(s)

Journal Title

Data Source

[Journal Article] Sparse Hilbert-Schmidt Independence Criterion Regression2020

Author(s)

Journal Title

Data Source

[Journal Article] Statistical analysis of sparse approximate factor models2020

Author(s)

Journal Title

DOI

Data Source

[Presentation] Sparse Hilbert-Schmidt Independence Regression Criterion2021

Author(s)

Organizer

Data Source

[Presentation] Sparse Hilbert-Schmidt Independence Regression Criterion2020

Author(s)

Organizer

Data Source

[Presentation] High-dimensional Sparse Multivariate Stochastic Volatility Models2020

Author(s)

Organizer

Data Source

[Presentation] High-dimensional Sparse Multivariate Stochastic Volatility Models2020

Author(s)

Organizer

Data Source

[Presentation] Sparse Hilbert-Schmidt Independence Regression Criterion2020

Author(s)

Organizer

Data Source

[Presentation] Long term asset allocation2019

Author(s)

Organizer

Data Source

[Presentation] Sparse Hilbert-Schmidt Independence Criterion Regression2019

Author(s)

Organizer

Data Source

[Presentation] The Finite Sample Properties of Sparse M-estimators with Pseudo-Observations2019

Author(s)

Organizer

Data Source

[Presentation] Statistical analysis of sparse approximate factor models2019

Author(s)

POIGNARD Benjamin ＰＯＩＧＮＡＲＤＢＥＮＪＡＭＩＮ

POIGNARD BENJAMIN ポイニャルベンジャミン