Strategies, Tactics, and Mindset Learned from "The Ph.D. Grind" Note: This is a Paper Reading for Philip Guo’s famous book “The Ph.D. Grind: A Ph.D. Student Memoir.” Main Strategies Be careful when choosing advisors and collaborators. Consider the background and 2023-12-31 Reflections #career
Linear Regression, Ridge Regression, Lasso Regression, and Kernel Ridge Regression Linear Regression Linear regression is a fundamental statistical model used in statistics and supervised machine learning. It establishes a linear relationship between a scalar response and one or mor 2023-12-24 Mathematics #machine-learning
Sarah Chasins' Works on PL and HCI Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice DomainInvestigative journalists and public defenders are crucial in scrutinizing and litigatin 2023-11-05 Research Notes #programming-languages #researcher-profile #hci
Nico Ritschel's Ph.D. Defense Summary Nico Ritschel‘s research focuses on refining block-based programming by integrating elements from visual programming to make it more accessible and effective for end-users, especially in the robotics 2023-10-13 Research Notes #programming-languages #defense-summary
Pre-MICCAI Workshop@UBC Observations and Gained Insights From the Pre-MICCAI Workshop@UBC website: The Pre-MICCAI Workshop is a dynamic and innovative platform that unites machine learning and medical computer vision. As a prelude to the prestigious MICCAI 2023-10-08 Research Notes #workshop-notes #medical-imaging
Understanding the Name, Structure, and Loss Function of the Variational Autoencoder Despite the intuitive appeal of variational autoencoders (VAEs), their underlying principles can be elusive. After extensive research across papers and online resources, I will summarize the core insi 2023-09-30 AI and Machine Learning #machine-learning