Yuko Kuroki (黒木 祐子 in Japanese)

My web page has been moved to https://sites.google.com/view/yuko-kuroki/ since February 1, 2023.


Assistant Professor,

Department of Computer Science,

Graduate School of Information Science and Technology, The University of Tokyo.

Prof. Hiroshi Imai's Laboratory.

Email: yukok -at- is.s.u-tokyo.ac.jp


Yuko Kuroki is a research associate at The University of Tokyo. Her research includes optimization, machine learning, and data mining especially related to graph problems. She received her Ph.D. (2021) from The University of Tokyo under the supervision of Prof. Masashi Sugiyama with the Dean's Award for Outstanding Achievement, Graduate School of Information Science and Technology. She is a visiting scientist at RIKEN Center for Advanced Intelligence Project (AIP), Imperfect Information Learning Team.


News

・2022/11/26: I gave an invited talk at 2022 Data-driven Optimization Workshop host by Microsoft Research Asia [link]

・2021/09/29: Our paper "Combinatorial Pure Exploration with Bottleneck Reward Function", joint work with Y. Du (leading author) & W. Chen, has been accepted to NeurIPS2021!

・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!

Research Interests

  • Statistical Machine Learning

-Combinatorial bandits, Weakly supervised learning

  • Combinatorial Optimization

-Approximation algorithms (e.g. Metric labeling problems, Hub network design problems, Hub location problems)

  • Graph Mining

-Densest subgraph discovery

  • Algorithmic Game Theory

-Stackelberg game

Awards

Educations

  • Ph.D. , March 2021：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 )

Research Grants/Projects


  • April 2021 -- present. MSRA Collaborative Research 2021, Microsoft Research Asia,

Title: Towards Optimal Combinatorial Online Learning under Uncertainty

Collaborator: Prof. Wei Chen

  • 2020/11~present: Strategic Basic Research Programs ACT-X, JST [link]

Title : "Learning from limited information and design of mathematical optimization algorithms"

  • 2019/12~2020/12: 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

Work Experience

  • 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


Teaching

The University of Tokyo

  • 2022 A1A2 (Undergraduate B3): Computational complexity theory (Information Science Exercise II, Department of Information Science, Faculty of Science)

  • 2022 S1S2 (Undergraduate B3): Discrete mathematics (Information Science Exercise I, Department of Information Science, Faculty of Science)

  • 2021 A1A2 (Undergraduate B3): Computational complexity theory (Information Science Exercise II, Department of Information Science, Faculty of Science)

  • 2021 S1S2 (Undergraduate B3): Discrete mathematics (Information Science Exercise I, Department of Information Science, Faculty of Science)

UTokyo Extension Data Science School