lingu log

Attending S4D

I will be attending Research Summer School on Statistics for Data Science at Caen University in Caen, France. I will update this post on the matter.

Reading list for S4D:


On the subject of ML optimizations:

  1. Schoenauer-Sebag, A., Schoenauer, M., & Sebag, M. (2017). 2. Stochastic Gradient Descent: Going As Fast As Possible But Not Faster. arXiv preprint arXiv:1709.01427.
  2. Fran├ža, G., & Bento, J. ADMM and Random Walks on Graphs.
  3. https://towardsdatascience.com/types-of-optimization-algorithms-used-in-neural-networks-and-ways-to-optimize-gradient-95ae5d39529f
  4. https://arxiv.org/pdf/1712.07897.pdf
  5. https://arxiv.org/pdf/1706.10207.pdf
  6. https://towardsdatascience.com/types-of-optimization-algorithms-used-in-neural-networks-and-ways-to-optimize-gradient-95ae5d39529f

On the subject of Probabilistic Modeling for ML:

  1. http://mlg.eng.cam.ac.uk/zoubin/talks/mit12csail.pdf

On the subject of Theory of Statistical Inference:

  1. http://www.ltcc.ac.uk/media/london-taught-course-centre/documents/Fundamental-Theory-of-Statistical-Inference-notes.pdf

On the subject of MM algorithms:

  1. https://www.stat.berkeley.edu/~aldous/Colloq/lange-talk.pdf
  2. https://arxiv.org/abs/1506.07613
  3. http://www.ece.ust.hk/~palomar/ELEC5470_lectures/11/slides_MM_algorithms.pdf
  4. https://www.stat.berkeley.edu/~aldous/Colloq/lange-talk.pdf