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:

Deepen theoretical understanding through practical application.

Engage in projects that align with your research focus area.

Criteria for Project Selection:

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

Should address a significant problem or explore an innovative concept.

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:

Research relevant papers and source code.

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

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.

Enhanced Outcomes:

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

After completion:

Enhance coding and project management skills.

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

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

Demonstrate teamwork and collaborative skills.

Resilience in Outcomes:

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)