stochastic_monk

100 ms·

1. 1021.▲
   by stochastic_monk 9y ago

   Actually, the Times on the whole does rather well. In fact, there are a number of times when I find that it works so hard to present views from several angles that it falls into offering false equivalency and pandering. [Off-topic: The bigg
2. 1022.▲
   by stochastic_monk 9y ago

   If I'm not mistaken, a Deep Belief Net or Deep Belief Machine would also be a generative model with enormously greater data efficiency. Comparing against CNNs is a red herring: the advantage of requiring less data to develop a model is
3. 1023.▲
   by stochastic_monk 9y ago

   I agree both that nurettin has a great point and that git is insufficient. A recent failure: I use some projects which fail to compile with clang or more recent gccs but happily compile with gcc4. Homebrew/linuxbrew don't let me h
4. 1024.▲
   by stochastic_monk 9y ago

   Very interesting; I've ignored random forests more than I should. Thank you! I won't comment on your methods except to say that comparing classification over linear PCA against a kernel PCA in linearly unseparable data isn't
5. 1025.▲
   by stochastic_monk 9y ago

   You're absolutely right. But this is still a huge step forward. There has been work on the VC dimension of neural networks for a long time (and it's been shown to be finite), which is a necessary but not sufficient condition for
6. 1026.▲
   by stochastic_monk 9y ago

   Herb Sutter's recent tips are more modern (and the backlog is being updated). Scott Meyers' Effective Modern C++ is a great successor to his Effective C++ book which spawned the whole "Effective *" snowclone books and co
7. 1027.▲
   Show HN: Threadsafe, SIMD-Accelerated HyperLogLog Implementation(github.com)

   5 points by stochastic_monk 9y ago|0 comments