Yuko Kuroki (黒木 祐子 in Japanese)
Department of Computer Science,
Graduate School of Information Science and Technology, The University of Tokyo.
Email: yukok -at- is.s.u-tokyo.ac.jp
I have completed Ph.D. degree under the supervision of Prof. Masashi Sugiyama at The University of Tokyo on March 2021. Before joining the PhD, I have studied combinatorial optimization with Prof. Tomomi Matsui in Tokyo Institute of Technology.
My research goal is to design efficient algorithms for motivated problems in practice and provide the theoretical guarantee based on optimization theory. My research interests range from machine learning, data mining, and optimization.
・2021/3/21: I have completed Ph.D. and received Dean's Award for Outstanding Achievement of Graduate School of Information Science and Technology, The University of Tokyo.
・2020/12/02: Our paper "Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback" has been accepted in AAAI2021! See you in online!
・2020/10/19: My Research Proposal for the Strategic Basic Research Programs ACT-X "Learning from limited information and design of mathematical optimization algorithms" is accepted!
・2020/06: Our paper "Online Dense Subgraph Discovery with Blurred-Graph Feedback" has been accepted in ICML2020! See you in online!
・2020/04: Our paper "Polynomial-time algorithms for multiple-arm identification with full-bandit feedback" has been accepted in Neural Computation!
・2019/12/25: I was selected as an awardee of Microsoft Research Asia Collaborative Research Program D-CORE 2020!
・I am going to attend WiML2019 and NeurIPS2019. I will present my recent work "Polynomial-time Algorithms for Multiple-arm Identification with Full-bandit Feedback" in WiML. See you in Vancouver!
・I received the Student Best Presentation Award at IBIS2019. [link] (Japanese only)
・ Our paper " Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation" has been accepted in IJCAI2019. See you in Macao!
Statistical Machine Learning
-Combinatorial bandits, Weakly supervised learning
-Approximation algorithms (e.g. Metric labeling problems, Hub network design problems, Hub location problems)
-Densest subgraph discovery
Algorithmic Game Theory
Dean's Award for Outstanding Achievement, Graduate School of Information Science and Technology, The University of Tokyo, March 2021.
Excellent Presentation Award Finalist 2020 Workshop on Information-Based Induction Sciences (IBIS2020), November 2020.
Microsoft Research Asia D-CORE (2020) Award, Dec. 25, 2019
The Student Best Presentation Award, The 22nd Information-based Induction Sciences (IBIS 2019), November 2019.
The 36th Student Thesis Award, The Operations Research Society of Japan, Sep. 2018, [abstract] .
Best Poster Presentation Award，Network science seminar，August 2017.
Presentation Award, Workshop on Optimization: Foundations and Frontiers, The Operations Research Society of Japan, May 2017
Presentation Award, Workshop on Optimization: Foundations and Frontiers, The Operations Research Society of Japan, May 2016
April 2018〜present：Ph.D. Student at Department of Computer Science, Graduate School of Information Science and Technology, University of Tokyo （Supervisor: Prof. Masashi Sugiyama ）
Master of Engineering, March 2018：School of Engineering, Department of Industrial Engineering and Economics, Tokyo Institute of Technology (Supervisor: Prof. Tomomi Matsui )
Bachelor of Engineering, March 2016：Undergraduate School of Engineering, Department of Social Engineering, Tokyo Institute of Technology (Supervisor: Prof. Tomomi Matsui )
2020/11~present: Strategic Basic Research Programs ACT-X, JST [link]
Title : "Learning from limited information and design of mathematical optimization algorithms"
2019/12~present: MSRA Collaborative Research Program (D-CORE 2020)
Title: Machine Learning with Blurred Supervision: Theory and Algorithm from Offline to Online
Collaborator : Prof. Wei Chen (MSRA Theory)
2018/04~ present: Grant-in-Aid for JSPS Research Fellow (DC1) [link]
Title: Multi-objective optimization on networks and its applications to machine learning
2020/04~2021/03: UTokyo Toyota-Dwango Scholarship
2018/08~2019/03: AIP Challenge Program, JST
Title (in Japanese): 信頼度の低いデータからの機械学習
2018/04~present: Research Fellow (DC1), The Japan Society for the Promotion of Science, Tokyo, Japan.
Part-timer, 2019/04~, RIKEN Center for Advanced Intelligence Project (AIP), Imperfect Information Learning Team
Trainee, 2018/07~2019/03, RIKEN Center for Advanced Intelligence Project (AIP), Imperfect Information Learning Team
Research Assistant, 2016/05~2018/03 JST, ERATO, Kawarabayashi Large Graph Project Global Research Center for Big Data Mathematics, National Institute of Informatics, Japan