4 ms·

Neural networks and a dive into Julia

64 points by glamp 12y ago

dnautics 12y ago
I am using Julia to casually participate in a bioinformatics contest (I have no bioinformatics background but I am pretty darned good at coding and biochemistry). The technique i'm using involves blasting a subset of the genome with neural nets, and I'll be damned if Julia isn't fast. I haven't benchmarked it against python, but basically the program is running a hybrid swarm optimization/gradient descent technique to find 20:5:1 neural nets; it is able to find test and optimize a swarm of 100 neural nets over 50 iterations in about 2 seconds on my rather slow laptop (2.3 GHz Core i3) A friend of mine is doing the same contest (using python) and his eyes popped out when I told him how efficient Julia was.
- supergirl 12y ago
  which contest?
  - dnautics 12y ago
    https://www.synapse.org/#!Synapse:syn1734172 https://www.synapse.org/#!Synapse:syn1734172
- jamesjporter 12y ago
  This sounds really cool; I'd love to see a blog post about it :)
  - dnautics 12y ago
    I would love to but i got a very late start on this and I'm coming up against a time crunch... I was without my laptop while traveling because I left it in the security line... also for HIPAA reasons I have to be very careful about what gets included in the git push, etc. etc. For various reasons it's a PITA so I might only do a blog post about it if it's successful, and after the contest is over.
- babayaga 12y ago
  Have your friend tried Cython or Numba? It's amazing what couple of extra lines can do with python code ;)
bch 12y ago
I'm pretty excited about Julia and integrating it into existing infrastructure[0]. The build process though -- even the "release" seems to insist on running git to pulldown code/data from the network -- if Julia devs/release-managers are reading -- what are odds of getting standalone distributions ? [0] https://news.ycombinator.com/item?id=7173137 https://news.ycombinator.com/item?id=7173137
- one-more-minute 12y ago
  We're actually working on static compilation right now, so that you'll be able to compile Julia code to a small binary and distribute it without the runtime. It should be completed over the summer.
  - dnautics 12y ago
    Is there any word on Julia for the arm? To use my programs on rpi As it is I have to convert to octave (not hard) but the for loops are slooow.
    - StefanKarpinski 12y ago
      Isaiah Norton recently got Julia minus some of the external libraries working on ARM [1], but there's still a lot of work to be done. But it is certainly not impossible. [1] https://github.com/JuliaLang/julia/issues/3134#issuecomment-41510527 https://github.com/JuliaLang/julia/issues/3134#issuecomment-...
      - dnautics 12y ago
        awesome! I know that BLAS is now working on ARM. My RPi debian distro came with mathematica.
  - bch 12y ago
    Unless I misread, I think you misinterpretted my question: what I'm wanting to do is compile a libjulia.so and link against it, and submit code to it and collect the results. Grabbing either the git master tip, or even .tgz "distribution" and trying to compile that results in git being fired up and pulling in _something_ new. Can that "something" be included in a distribution so I can effectively just: ./configure; make; make install without git, and without hauling down more code/data over the network ?
michaelochurch 12y ago
Interesting. OP (if you're around): I noticed in the confusion matrix that everything was classified to the middle classes (5, 6, 7). That makes sense because the 3s, 4s, and 8s are rare and "true 8s" are still most likely to have a high probability on the 7 class, because there are far more 7s in the data. Did you analyze approximate correctness for the probabilities, or consider sampling from the computed probabilities rather than classifying to the highest one, to see where that led?
- ericchiang 12y ago
  Hi there. That ml problem is more for example than for rigor. In fact that particular problem would probably be better suited for other algorithms (eg, random forest). My background's in biomedical imaging, so I'm quite fond of problems with skewed class distributions. Though I didn't have time to explore this particular one further. The code's all openly available if you want to give it a go though :)

64 points by glamp 12y ago

I am using Julia to casually participate in a bioinformatics contest (I have no bioinformatics background but I am pretty darned good at coding and biochemistry). The technique i'm using involves blasting a subset of the genome with neural nets, and I'll be damned if Julia isn't fast. I haven't benchmarked it against python, but basically the program is running a hybrid swarm optimization/gradient descent technique to find 20:5:1 neural nets; it is able to find test and optimize a swarm of 100 neural nets over 50 iterations in about 2 seconds on my rather slow laptop (2.3 GHz Core i3) A friend of mine is doing the same contest (using python) and his eyes popped out when I told him how efficient Julia was.

supergirl 12y ago
which contest?
- dnautics 12y ago
  https://www.synapse.org/#!Synapse:syn1734172 https://www.synapse.org/#!Synapse:syn1734172
jamesjporter 12y ago
This sounds really cool; I'd love to see a blog post about it :)
- dnautics 12y ago
  I would love to but i got a very late start on this and I'm coming up against a time crunch... I was without my laptop while traveling because I left it in the security line... also for HIPAA reasons I have to be very careful about what gets included in the git push, etc. etc. For various reasons it's a PITA so I might only do a blog post about it if it's successful, and after the contest is over.
babayaga 12y ago
Have your friend tried Cython or Numba? It's amazing what couple of extra lines can do with python code ;)

bch 12y ago

I'm pretty excited about Julia and integrating it into existing infrastructure[0]. The build process though -- even the "release" seems to insist on running git to pulldown code/data from the network -- if Julia devs/release-managers are reading -- what are odds of getting standalone distributions ? [0] https://news.ycombinator.com/item?id=7173137 https://news.ycombinator.com/item?id=7173137

one-more-minute 12y ago
We're actually working on static compilation right now, so that you'll be able to compile Julia code to a small binary and distribute it without the runtime. It should be completed over the summer.
- dnautics 12y ago
  Is there any word on Julia for the arm? To use my programs on rpi As it is I have to convert to octave (not hard) but the for loops are slooow.
  - StefanKarpinski 12y ago
    Isaiah Norton recently got Julia minus some of the external libraries working on ARM [1], but there's still a lot of work to be done. But it is certainly not impossible. [1] https://github.com/JuliaLang/julia/issues/3134#issuecomment-41510527 https://github.com/JuliaLang/julia/issues/3134#issuecomment-...
    - dnautics 12y ago
      awesome! I know that BLAS is now working on ARM. My RPi debian distro came with mathematica.
- bch 12y ago
  Unless I misread, I think you misinterpretted my question: what I'm wanting to do is compile a libjulia.so and link against it, and submit code to it and collect the results. Grabbing either the git master tip, or even .tgz "distribution" and trying to compile that results in git being fired up and pulling in _something_ new. Can that "something" be included in a distribution so I can effectively just: ./configure; make; make install without git, and without hauling down more code/data over the network ?

michaelochurch 12y ago

Interesting. OP (if you're around): I noticed in the confusion matrix that everything was classified to the middle classes (5, 6, 7). That makes sense because the 3s, 4s, and 8s are rare and "true 8s" are still most likely to have a high probability on the 7 class, because there are far more 7s in the data. Did you analyze approximate correctness for the probabilities, or consider sampling from the computed probabilities rather than classifying to the highest one, to see where that led?

ericchiang 12y ago
Hi there. That ml problem is more for example than for rigor. In fact that particular problem would probably be better suited for other algorithms (eg, random forest). My background's in biomedical imaging, so I'm quite fond of problems with skewed class distributions. Though I didn't have time to explore this particular one further. The code's all openly available if you want to give it a go though :)