📅 2025-02-27 — Session: Ethical and Technical Reflections on Data Use
🕒 15:10–15:35
🏷️ Labels: Ethics, Deep Learning, Data Privacy, Regularization, Transfer Learning
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to explore both ethical and technical considerations of data use, particularly focusing on census data, deep learning techniques for a thesis, and regularization strategies for structured data.
Key Activities
- Reflected on the ethical implications of making census databases public and the responsibilities of using publicly available data.
- Evaluated the use of greedy layer-wise pretraining and transfer learning for deep learning thesis applications.
- Analyzed regularization strategies for population-structured data and assessed the relevance of Hinton et al. (2006) paper to current data work.
Achievements
- Developed insights into ethical data use and legal considerations for researchers.
- Identified key deep learning techniques relevant to thesis work.
- Highlighted effective regularization strategies for structured data.
Pending Tasks
- Further exploration of alternative learning approaches in deep learning.
- Continued assessment of ethical frameworks for data sharing.