Current interest areas include
- algorithms for big data
- machine learning: supervised, unsupervised, reinforcement
- social networks
- computational finance
The premise of learning is that you want to understand some process,
but you cannot solve this problem mathematically
or analytically; instead, you have data that represents your process and
you would like to learn/infer this process from the data; and, be confident
that you succeeded (or failed). Ultimately you will take some action
based on your learned process, and you would like to take the correct action.
This is a very broad premise, and it is
no surprise that there are many applications.
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