Hi, I am doing my PHD thesis on large scale machine learning e.g Online learning, batch and mini batch learning.
Could somebody help me with ideas especially in the context of Spark and to the above learning methods. Some ideas like improvement to existing algorithms, implementing new features especially the above learning methods and algorithms that have not been implemented etc. If somebody could help me with some ideas it would really accelerate my work. Plus few ideas on research papers regarding Spark or Mahout. Thanks in advance. Regards
