I think this article exemplifies the difference between the kinds of things you see codified in books and on the internet, versus what's active research and well known folk lore in academia. And maybe it highlights the substandard search mechanisms for published research, or the difficulty of learning from published research papers. But it's definitely not about neglect, at least not for most of the topics listed in the article.
For example, the recent AAAI 2014 conference had a bunch of papers on online algorithms for various problems. [1] Likewise, COLT had five or so papers on online learning. [2] Same with KDD [3], SODA [4], and the many other conferences this year that accept papers about ML.
And learning in the presence of noise? Unsupervised learning? Feature engineering? I am literally doing multiple research projects in all of these areas right now! The only way I can imagine that you think they're neglected is that you just don't know where to look for them, because these topics are all over the place in my world. For example, one common term for "feature engineering" is "representation learning," and this was a big topic at this year's SDM conference, specifically w.r.t. data mining in networks.
Why can't you find a book you like for topic X? Maybe it's because researchers have little incentive to write books. You folks in industry could fix that. What with all your ridiculous market valuations of various mobile apps, surely you could scrape together enough funding to convince the experts in their field to write a book.
For example, the recent AAAI 2014 conference had a bunch of papers on online algorithms for various problems. [1] Likewise, COLT had five or so papers on online learning. [2] Same with KDD [3], SODA [4], and the many other conferences this year that accept papers about ML.
And learning in the presence of noise? Unsupervised learning? Feature engineering? I am literally doing multiple research projects in all of these areas right now! The only way I can imagine that you think they're neglected is that you just don't know where to look for them, because these topics are all over the place in my world. For example, one common term for "feature engineering" is "representation learning," and this was a big topic at this year's SDM conference, specifically w.r.t. data mining in networks.
Why can't you find a book you like for topic X? Maybe it's because researchers have little incentive to write books. You folks in industry could fix that. What with all your ridiculous market valuations of various mobile apps, surely you could scrape together enough funding to convince the experts in their field to write a book.
[1]: http://www.aaai.org/Conferences/AAAI/2014/aaai14accepts.php [2]: http://orfe.princeton.edu/conferences/colt2014/the-conferenc... [3]: http://www.kdd.org/kdd2014/program.html [4]: http://www.siam.org/meetings/da14/da14_accepted.pdf