Blogs are a fun way to communicate.
But beyond being fun, they seem to be a very promising tool for researchers. Indeed, I realize everyday that the core activity of a researcher is not to think but to share ideas with others. I noticed that productivity is a monotone function of the number of conferences you attend, papers you read or time you spend discussing with others.
So the main goal of this blog is to increase the "ideas traffic" over the internet about the topic I am interested in: Machine Learning.
To be more specific, there are three areas in which I would like to actively start or participate in discussions:
- Philosophy: as a relatively young scientific field, Machine Learning lacks unity and foundations. This is fortunate because it prevents, to some extent, people from being too dogmatic. The overall atmosphere is very open to various sources of inspiration and to cross-fertilization with remote fields. Ideally, foundations should be built in a way that does not restrict this openness.
- Theory: while the first item is about philosophical foundations, the same is true of the theoretical foundations. There is already a large litterature about theoretical topics of Machine Learning, but there is no such thing as a Machine Learning Theory. Of course, one may argue that there is no need for a single theory (or that it is not possible to unify this diverse field), but this is a matter of discussion, debate and/or research.
- Practice: finally, I would like to discuss and exchange ideas about practical aspects. In this topic, I include both the design of algorithms, their implementation and the various problems that they may be applied to.
Overall, I hope this blog will not only be a way for me to publish ideas but will be enriched by others' contributions and thus be profitable to others in the ML community.