Matsushima Shin 松島慎

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松島慎マツシマシン

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Researcher Number	90721837
Other IDs
Affiliation (Current)	2025: 東京大学, 大学院総合文化研究科, 准教授 2025: 東京大学, 大学院情報理工学系研究科, 准教授
Affiliation (based on the past Project Information) *help	2023: 東京大学, 大学院総合文化研究科, 准教授 2021: 東京大学, 大学院総合文化研究科, 准教授 2019 – 2021: 東京大学, 大学院情報理工学系研究科, 准教授 2017: 東京大学, 大学院情報理工学系研究科, 常勤講師 2017: 東京大学, 大学院総合文化研究科, 常勤講師 2016: 東京大学, 大学院情報理工学系研究科, 助教 2014 – 2015: 東京大学, 情報理工学(系)研究科, 助教
Review Section/Research Field	Principal Investigator Basic Section 61030:Intelligent informatics-related / Intelligent informatics
Keywords	Principal Investigator 凸最適化 / 機械学習 / スパースモデリング / 解釈可能性 / 統計的機械学習 / 部分空間クラスタリング / クラスタリング / 国際情報交換 / ビッグデータ / データマイニング / SVM / 大規模学習 / スパース学習

Research Projects
(3 results)
Research Products
(6 results)

Large-scale sparse learning using asynchronous architecture for interpretable modelPrincipal Investigator
- Principal Investigator
  
  松島慎
- Project Period (FY)
  2023 – 2025
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  The University of Tokyo
Construction of convex optimization schemes for large-scale subspace clustering and its theoretical guaranteesPrincipal Investigator
- Principal Investigator
  
  Matsushima Shin
- Project Period (FY)
  2019 – 2021
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  The University of Tokyo
Architectures and optimization algorithms for machine learning from big dataPrincipal Investigator
- Principal Investigator
  
  Matsushima Shin
- Project Period (FY)
  2014 – 2017
- Research Category
  
  Grant-in-Aid for Young Scientists (B)
- Research Field
  
  Intelligent informatics
- Research Institution
  The University of Tokyo

All 2019 2017 2016 2014

All Journal Article Presentation

[Journal Article] Asynchronous Feature Extraction for Large-Scale Linear Predictors2016
- Author(s)
  Shin Matsushima
- Journal Title
  
  Lecture Notes in Computer Science
  
  Volume: 9851 Pages: 604-618
- DOI
  10.1007/978-3-319-46128-1_38
- ISBN
  9783319461274, 9783319461281
- Peer Reviewed / Acknowledgement Compliant
- Data Source
  KAKENHI-PROJECT-26730114
[Presentation] Selective Sampling-based Scalable Sparse Subspace Clustering2019
- Author(s)
  Shin Matsushima, Maria Brbic
- Organizer
  Conference on Neural Information Processing Systems
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-19K20336
[Presentation] 大規模な線形予測器のための非同期特徴抽出スキーム2017
- Author(s)
  松島慎
- Organizer
  統計的モデリングと計算アルゴリズムの数理と展開
- Place of Presentation
  名古屋大学（愛知県）
- Year and Date
  2017-02-18
- Data Source
  KAKENHI-PROJECT-26730114
[Presentation] Distributed Stochastic Optimization of Regularized Risk via Saddle-point Problem2017
- Author(s)
  Shin Matsushima, Hyokun Yun, Xinhua Zhang, S.V.N. Vishwanathan
- Organizer
  In Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Lecture Notes in Computer Science (LNCS)
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26730114
[Presentation] Asynchronous Feature Extraction for Large-Scale Linear Predictors2016
- Author(s)
  Shin Matsushima
- Organizer
  ECML PKDD: Joint European Conference on Machine Learning and Knowledge Discovery in Databases
- Place of Presentation
  Riva del Garda, Italy
- Year and Date
  2016-09-19
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-26730114
[Presentation] 正則化付き経験リスク最小化における分散最適化法2014
- Author(s)
  松島慎
- Organizer
  日本応用数理学会年会
- Place of Presentation
  政策研究大学院大学（東京都）
- Year and Date
  2014-09-05
- Data Source
  KAKENHI-PROJECT-26730114

Matsushima Shin 松島 慎

松島 慎 マツシマ シン

Research Projects

Research Products

Large-scale sparse learning using asynchronous architecture for interpretable modelPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Construction of convex optimization schemes for large-scale subspace clustering and its theoretical guaranteesPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Architectures and optimization algorithms for machine learning from big dataPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Research Field

Research Institution

[Journal Article] Asynchronous Feature Extraction for Large-Scale Linear Predictors2016

Author(s)

Journal Title

DOI

ISBN

Data Source

[Presentation] Selective Sampling-based Scalable Sparse Subspace Clustering2019

Author(s)

Organizer

Data Source

[Presentation] 大規模な線形予測器のための非同期特徴抽出スキーム2017

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] Distributed Stochastic Optimization of Regularized Risk via Saddle-point Problem2017

Author(s)

Organizer

Data Source

[Presentation] Asynchronous Feature Extraction for Large-Scale Linear Predictors2016

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

[Presentation] 正則化付き経験リスク最小化における分散最適化法2014

Author(s)

Organizer

Place of Presentation

Year and Date

Data Source

Matsushima Shin 松島慎

松島慎マツシマシン