Statitical Learning Theory (2016), Graduate School of Informatics, Kyoto University
Marco Cuturi, Hisashi Kashima
Monday, 8:45-10:15 / Research bldg. 8, Lecture room 4

yTopicsz
- Advaced topics of supervised learning
- Unsupervised learning

yLecture Slidesz
1. Multi-class classification and structured output prediction
2. Semi-supervised, active, and transfer learning
3. Model evaluation
4. Sparsity
5. On-line learning

yReferencesz
- Competition site for homeworks: University of Big Data
- Lecture slides for the previous years: 2014, 2015