Machine learning and learning theory research
A big part of doing research is imagining how things could be different, and then trying to figure out how to get there. A big part of science fiction is imagining how things could be different, and then working through the implications. Because of the similarity here, reading science fiction can sometimes be helpful in …
At many points in research, you face a choice: should I keep on improving some old piece of technology or should I do something new? For example: Should I refine bounds to make them tighter? Should I take some learning theory and turn it into a learning algorithm? Should I implement the learning algorithm? Should …
If we accept that bad reviewing often occurs and want to fix it, the question is “how”? Reviewing is done by paper writers just like yourself, so a good proxy for this question is asking “How can I be a better reviewer?” Here are a few things I’ve learned by trial (and error), as a …
The funding of research (and machine learning research) is an issue which seems to have become more significant in the United States over the last decade. The word “research” is applied broadly here to science, mathematics, and engineering. There are two essential difficulties with funding research: Longshot Paying a researcher is often a big gamble. …
Since learning is far from an exact science, it’s good to pay attention to basic intuitions of applied learning. Here are a few I’ve collected. Integration In Bayesian learning, the posterior is computed by an integral, and the optimal thing to do is to predict according to this integral. This phenomena seems to be far …