Hiroki Naganuma

学習リソース

• Deep learning and Physics
  • 深層学習の汎化の謎をめぐって
• Mila の Lecture
  • IFT 6132 – Advanced Structured Prediction and Optimization
  • IFT 6135 - Representation Learning
  • IFT 6390: Fundamentals of machine learning
  • IFT 6085: Theoretical principles for deep learning
  • IFT 6760B & 6167: Neural Scaling Laws and Foundation Models
  • IFT 6760A: Matrix and tensor factorization techniques for machine learning
  • IFT 6756: Game Theory and ML course
  • MATH 80600A: Machine Learning II: Deep Learning and Applications
  • COMP 579: Reinforcement Learning
  • COMP 551: Applied Machine Learning
  • ECSE 506: Stochastic Control and Decision Theory
• Vector Institute の Lecture
  • CSC2541: Topics in Machine Learning: Neural Net Training Dynamics
  • CSC 311: Introduction to Machine Learning
• MLSS: Machine Learning Summer School

• 東京大学の資料

  • Deep Learning Reading Group
  • PRML, Pattern Recognition and Machine Learning
  • 今泉允聡先生の資料
  • 鈴木大慈先生の資料
    • 深層学習および機械学習の数理
    • カーネル法と深層学習の数理
• Mila の Predoc の勉強資料置き場 (上記全てが範囲)