Future Wisdom @ GSAIS (Shishu-Kan) , Kyoto U.

Schedule

• Default: 1:15 - 2:45 pm, Wednesday
• Room: ???

This initiative aims to replace traditional book-based learning with hands-on, collaborative projects that allow you to explore advanced concepts in Graph Learning and Image Processing. Here are the detailed guidelines and instructions to ensure your project is well-structured and aligns with the initiative's goals:

Total Members: 7 students, divided into two specialized groups.

Group A: students focusing on Graph Learning Research.

Group B: students focusing on Image Processing Research.

The primary objective is to foster a shift from passive learning to active project-based learning. This approach enables you to:

a. Deepen theoretical understanding through practical application.

b. Engage in projects that align with your research focus area.

Criteria for Project Selection:

a. Relevance to the group’s specific focus area (Graph Learning or Image Processing).

b. Should address a significant problem or explore an innovative concept.

c. Feasible to complete within a semester.

Example Project Idea: Using Neural Architecture Search to find the best architecture for image classification.

Timeline: Projects must be completed within one semester.

Collaboration Platform: Use GitHub for version control Roles and Responsibilities:

All Members:

a. Research relevant papers and source code.

b. Contribute to the project’s codebase, documentation, and other materials on GitHub.

c. Participate in weekly meetings to discuss progress and address challenges.

Individual Responsibilities:

Literature Review: Each member is assigned specific resources to review and present summaries.

Code Implementation: Members focus on different modules or features to ensure full project coverage.

Minimum Outcome: Successful replication of a recent research paper to code implementation.

Desired Outcomes (If possible):

Potential publication of robust and novel results in academic journals or conferences.

After completion:

a. Enhance coding and project management skills.

b. Develop critical thinking and problem-solving abilities through real-world applications.

c. Build a portfolio on GitHub to showcase skills to potential employers.

d. Demonstrate teamwork and collaborative skills.

Resilience in Outcomes:

a. Even if the project is not publishable, it serves as a valuable addition to your professional portfolio.

Progress Tracking: Use GitHub Issues and Projects to manage tasks, milestones, and deadlines.

Regular Check-ins: Weekly meetings for updates, insights, and problem resolution.

Final Presentation: At the semester's end, present the project outcomes, highlighting achievements, challenges, and lessons learned.

Thank you. Enjoy Learning

Schedule

• Default: 1:15 - 2:45 pm, Monday
• Room: 121/122 実習室
• April 8, 15, 22
• May 13, 20, 27
• June 3, 10, 17, 24
• July 1, 22, 29

Book

• https://www.cs.mcgill.ca/~wlh/grl_book/ (each time about 10 pages)