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> In academia, who the heck gets a doctorate for advancements in cleaning up arbitrary data to feed into ML models Well - Alex Ratner [stanford], for one: htt
by dgacmu 7y ago
> In academia, who the heck gets a doctorate for advancements in cleaning up arbitrary data to feed into ML models
Well - Alex Ratner [stanford], for one: https://ajratner.github.io/ https://ajratner.github.io/
And several of Chris Re's other students have as well: https://cs.stanford.edu/~chrismre/ https://cs.stanford.edu/~chrismre/
Trifacta is Joseph Hellerstein's [berkeley] startup for data wrangling: https://www.trifacta.com/ https://www.trifacta.com/
Sanjay Krishnan [berkeley]: http://sanjayk.io/ http://sanjayk.io/
- devonkim 7y agoI was asking somewhat rhetorically but am glad to see that there’s some serious efforts going into weak supervision. At the risk of goalpost moving, I am curious who besides those in the Bay Area at the cutting edge are working on this pervasive problem? My more substantive point is that given the massive data quality problem among the ML community I would expect these researchers to be superhero class but why aren’t they?
- dgacmu 7y ago... they are? There are a lot of people tackling bits and pieces of the problem. Tom Mitchell's NELL project was an early one, using the web in all its messy glory...http://rtw.ml.cmu.edu/rtw/ http://rtw.ml.cmu.edu/rtw/ Lots of other folks here (CMU). Particularly if you add an active learning. Hard messy problem that crosses databases and ML.