4 ms·
Those are really old results. They should compare to this one: https://arxiv.org/pdf/1511.06581.pdf https://arxiv.org/pdf/1511.06581.pdf
by nivwusquorum 9y ago
Those are really old results. They should compare to this one: https://arxiv.org/pdf/1511.06581.pdf https://arxiv.org/pdf/1511.06581.pdf
- higgsfield 9y agothis is old too
- csl 9y agoHow can the results be old when the paper is from 2017?
- aqsalose 9y agoThey are comparing their genetic programming results with a deep learning paper published in 2015. [1] [1] https://www.nature.com/nature/journal/v518/n7540/abs/nature14236.html https://www.nature.com/nature/journal/v518/n7540/abs/nature1...
- phoe-krk 9y agoWhat a time to live in, when papers from 2015 are "really old" in 2017.
- amelius 9y agoIt highly depends on the field you're in though.
- baq 9y ago1 deep learning year is about 49 dog years.
- posterboy 9y agoWhat is "exponential growth"!
- sk0g 9y agoIt's more logarithmic, isn't it? Right now we're at the beginning stage, where there's massive discoveries and changes happening, but in say, 50 years time, there won't be much changing year-to-year.
- jcranberry 9y agoLogarithmic or logistic?
- nrtd 9y agoI have not read the papers but from a quick glance at the tables the GP results are still better.