7:00 – 4:30 VTX

• Learning: Sparse Spaces, Phonology
  • Structure and Interpretation of Computer Programs – (constraints/propagators)
  • Pick a positive example to start learning (seed)
  • Generalize by matching the minimum attributes that allow the difference to be observed.
  • High-dimensional sparse space can more easily be separated with a hyperplane.
    • Sparse Representations for Fast, One-Shot Learning
  • Artificial Intelligence–A Personal View (Marr’s catechism)
    • A good representation makes the right things explicit and exposes constraints. A representation that allows for local rather than global identification is better.
• Spring end scrum
• Spent the rest of the day getting my new machine running. Almost there!