Rchr
J-GLOBAL ID：201801012309163342
Update date: Apr. 09, 2024
Takimoto Eiji
タキモト エイジ | Takimoto Eiji
Contact this researcher
You can send email directly to the researcher.
Affiliation and department：
Kyushu University
About Kyushu University
Search "Kyushu University"
Research field (1)：
Information theory
Research keywords (4)：
Algorithm
, Computation Theory
, Online Decision Making
, Computational Learning Theory
Research theme for competitive and other funds (28)：
2023 - 2027 最適化問題の圧縮表現に基づく効率的最適化スキームの確立
2022 - 2026 Online Desision Making Methods for Various Problems and Criteria
2020 - 2025 アルゴリズム基礎理論の追究・発展
2020 - 2025 Research Initiatives on Algorithmic Foundations for Social Advancement
2019 - 2023 データの学習容易性解析に基づく実ケース学習理論の確立
2018 - 2023 情報爆縮に基づくIoTデータ処理基盤の構築
2019 - 2022 Optimization based on discrete structure representations
2015 - 2019 Online Decision Making Based on Random Sampling
2013 - 2018 Information Implosion Foundational Technology
2012 - 2017 Approach from learning theory toward understanding the limitations of computation
2012 - 2017 A Multifaced Approach Toward Understanding the Limitations of Compuation
2013 - 2016 Foundations for Combinatorial Online Prediction
2011 - 2015 Online Decision Making by Convex Optimization
2010 - 2012 Foundational technology for light-weight XML-DBMS based on very fast compressed data stream processing
2008 - 2010 Practical approach to self-constructive learning on subjects on computer science
2008 - 2010 Learning non-linear concepts based on random projection
2005 - 2007 生体情報処理における深層計算と表層計算に関する研究
2004 - 2007 オンライン予測の手法を用いた意思決定モデルに関する研究
2003 - 2005 Computational principal on how parts and wholes cooperate and conflict
2003 - 2004 Dimensionality Reduction for Designing Online Algorithms
2001 - 2002 オンライン予測における次元圧縮に関する研究
2001 - 2002 On-line learning algorithm for organizing data based on generalized entropy
1998 - 1999 動的計画法に基づくオンライン予測に関する研究
1998 - 1998 ブースティング技術を用いた知識発見アルゴリズムに関する研究
1995 - 1995 学習過程における適応のモデル化に関する研究
1994 - 1994 学習過程における適応のモデル化に関する研究
1993 - 1994 Efficient learning algorithms based on infomation compression
1993 - 1993 学習過程における適応のモデル化とパターン認識における個人差の問題への応用
Show all
Papers (99)：
Ryotaro Mitsuboshi, Kohei Hatano, Eiji Takimoto. Solving Linear Regression with Insensitive Loss by Boosting. IEICE Trans. Inf. Syst. 2024. 107. 3. 294-300
Xuanke Jiang, Sherief Hashima, Kohei Hatano, Eiji Takimoto. Online Job Scheduling with K Servers. IEICE Trans. Inf. Syst. 2024. 107. 3. 286-293
Yiping Tang, Kohei Hatano, Eiji Takimoto. Rotation-Invariant Convolution Networks with Hexagon-Based Kernels. IEICE Trans. Inf. Syst. 2024. 107. 2. 220-228
Sherief Hashima, Kohei Hatano, Eiji Takimoto, Ehab Mahmoud Mohamed. Budgeted Thompson Sampling for IRS Enabled WiGig Relaying. Electronics. 2023. 12. 5. 1146-1-1146-13
Ryotaro Mitsuboshi, Kohei Hatano, Eiji Takimoto. An Improved Metarounding Algorithm via Frank-Wolfe. CoRR. 2023. abs/2310.12629
ｍore...
MISC (57)：
Ryohei Nagaura, Kohei Hatano, Eiji Takimoto. Combinatorial bandit prediction with relaxation-based approximation algorithm. SIG Technical Reports. 2018. 2018-AL-167. 4. 1-4
Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai, Akiko Takeda. Learning theory and algorithms for shapelets and other local features. NIPS Time Series Workshop 2017. 2017
森富 賢一郎, 畑埜 晃平, 瀧本 英二. Tighter generalization bounds for matrix completion based on non-negative matrix factorization with norm constraints (情報論的学習理論と機械学習). 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報. 2017. 116. 500. 1-8
Daiki Suehiro, Kengo Kuwahara, Kohei Hatano, Eiji Takimoto. Time Series Classification Based on Random Shapelets. 2016
永浦 良平, 畑埜 晃平, 瀧本 英二. Bandit Algorithm For k-Sets Based On Projection And Decomposition. 電子情報通信学会技術研究報告 = IEICE technical report : 信学技報. 2016. 116. 121. 225-229
ｍore...
Books (1)：
オンライン予測 (機械学習プロフェッショナルシリーズ)
講談社 2016 ISBN:4061529226
Lectures and oral presentations (10)：
差集合演算の導入による非決定性ZDDの拡張と集合間類似検索への応用
(冬のLAシンポジウム 2023)
Online Job Scheduling with k Servers
(2023)
決定ダイアグラムに基づく拡張定式化
(第25回情報論的学習理論ワークショップ(IBIS 2022) 2022)
フランク・ウルフ法としてのブースティング
(第25回情報論的学習理論ワークショップ(IBIS 2022) 2022)
Compressed ERLPBoost
(2022)
ｍore...
Work history (5)：
2008/04 - 現在 Kyushu University Graduate School and Faculty of Information Science and Electrical Engineering Professor
2007/04 - 2008/03 Tohoku University Graduate School of Information Science Associate Professor
1998/12 - 2007/03 Tohoku University Graduate School of Information Science Associate Professor
1993/06 - 1998/11 Tohoku University Graduate School of Information Science Assistant Professor
1991/04 - 1993/05 Tohoku University Faculty of Engineering Assistant Professor
Awards (1)：
2018/03 - WALCOM 2018 Best Paper Award: Boosting over Non-deterministic ZDDs
※ Researcher’s information displayed in J-GLOBAL is based on the information registered in
researchmap
.
For details, see here
.
Return to Previous Page
TOP
BOTTOM
