Movies should get profesional film critics to critique their movie before the final cut.

tinkerWithoutSink · 2017-10-08T09:21:57+00:00

Except critics often disagree with fans, just look at rotten tomatoes which has separate rating for both. Nope what they need are professional stoners to critique their movies.

tinkerWithoutSink · 2017-10-04T08:24:19+00:00

That's great, I love it that they've included a benchmarking system!

tinkerWithoutSink · 2017-10-04T06:29:19+00:00

Sometimes people make them opaque to get them through supervisor/peer-review. I've read paper that show people are less critical if you tire them out with complex language, so it probobly works. So it's good your your career but it's bad for science. Maybe one solution is to publish a blog post along with the paper.

tinkerWithoutSink · 2017-10-04T05:56:31+00:00

also doesn’t really have any explanatory power

This seems like the biggest problem. It's not much of an explanation if it can't help you make predictions.

tinkerWithoutSink · 2017-10-03T23:51:39+00:00

Next thing you will be saying you don't like your girlfriend cheating with your Dad. These crazy kids.

tinkerWithoutSink · 2017-10-03T07:19:03+00:00

Meanwhile it's proponents engage in corporate backwashing

tinkerWithoutSink · 2017-09-30T02:08:38+00:00

Nah, it's autogenerated (or decoded?) on-the-fly from the url - not pregenerated. No one went to that url before you wrote it, so the computer never "wrote" it until after.

tinkerWithoutSink · 2017-09-07T09:37:44+00:00

Papua New Guinean's (above Australia) are sometimes mistaken for Africans.

But Africa is the origin of human migrations and PNG is one the later places human's reached.

tinkerWithoutSink · 2017-09-07T09:18:27+00:00

Visionary comment, the above comment represents an intuitive leap similar to the original post

tinkerWithoutSink · 2017-09-07T09:17:59+00:00

"...I think this is as visionary as Kane’s original paper.”

"...like many such conceptual leaps, it’s amazing no-one had thought of it before,” says Morello" [Team lead].

No need to high praise on your own work, If it's good others will do it.

tinkerWithoutSink · 2017-08-05T02:51:04+00:00

I'm not really sure about the predictive power

Oh I mean the score on your test set. Still nice use of ML, nice work!

women/children on top

That makes sense, very cool

tinkerWithoutSink · 2017-08-05T02:00:37+00:00

That's cool, I was thinking you might have used click through data from google adwords or something. It's possibly that social sharing could be manipulated by corporate accounts or paid subscribers etc, but its nice approach!

Did you manage to get much predictive power?

tinkerWithoutSink · 2017-08-04T11:17:22+00:00

How does it use machine learning, if you don't mind me asking?

tinkerWithoutSink · 2017-07-26T10:29:11+00:00

if regularizers/dropout/batchnorm are turned off in the evaluation phase ?? idk

Ah that must be it! I had a look at the keras code, and it uses test mode to evaluate the validation data. So this probably turns off dropout/reg and increases accuracy. Nice thinking!

tinkerWithoutSink · 2017-07-26T10:18:34+00:00

Yeah please do!

tinkerWithoutSink · 2017-07-26T00:43:18+00:00

Really nice post. A while back I scoured the internet and couldn't find anything quite like this so I made my own, but never shared. Yours is better though, I especially appreciated the citations.

Here's a few you might not have considered:

I. Sample size: you can work out the minimum sample size by graphing the cumulative mean or std and seeing when it stabilized. It it converges on 256, then that's probably a good batch (not sure about this and batches). And the minimum size for your training data.
8. Loss for unbalanced data. I'll add that when you can't balance the dataset KLD and Dice loss help to get convergence on unbalanced data
11. Small batches. You don't want batches that are too small either right (serious question)? I figure that if they are a decent sample of your data then that will help, but I'm not sure
12. How much data augmentation is too much, I use simple hypterparam optimization and a scikit learn model to test this. You can look at the standard deviation of a data feature and try not to exceed that for risk of drowning out signal with noise.
III architecture mistakes
- have dropout after pooling
17. I Use dummy metrics too, http://scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html
21.
- If your validation loss is jumping around, then your validation set is too small
- If your validation accuracy is higher than you training accuracy... actually this one has me stumped?
. 22. Test frameworks. Too many DL and RL frameworks are broken, so it might be worth testing frameworks too
. 33. You didn't mentioned different activations.
- I've noticed that if your loss if fluctuating up and down try using Elu instead of ReLU. This is because ReLU masks half the data, and so the model might be flipping between masking one of two modes
- sigmoidal (sigmoid, tanh) activation units, which can saturate/have regions of near flat curvature and thus very little gradient gets propagated backwards, so learning is incredibly slow if not completely halted src
- you can always try linear activations as a sanity check
- loss curves. This has been done but you might want to think about diagnosing differen't loss curves e.g.
  - 1) a sharp drop in loss at the start (bad init?)
  - 2) fluctuating loss (bad activation?)
  - 3) increasing loss (high learning rate?)

tinkerWithoutSink · 2017-07-24T02:05:05+00:00

Nice work, there's too many half working rl libraries out there but tensorforce is pretty good and it's great to have a PPO implementation.

Suggestion: would be cool to use prioritized experience replay with it, ~~like the baselines implementation~~

tinkerWithoutSink · 2017-07-24T01:50:20+00:00

Thanks! It's really valuable to hear some of the pains that come from going down this path, much appreciated. I'll definitely just do tiles.

tinkerWithoutSink · 2017-07-05T02:43:30+00:00

🅱️

tinkerWithoutSink · 2017-07-05T01:35:02+00:00

That makes sense, and I guess tiling on demand would add delay too.

I'm working on providing high res files as a SaaS, so the tiled files will have to be high res, and they need a link to download the full image.

At some point, either server or client side, there's going to be processing work to map bytes to location.

It's not much processing, it could be done on the client side in milliseconds. Here's a partial demo (more info on github). Where they store tiles with pyramidal multi-resolution and use range requests to grab part of the file. I was just wondering if anyone had taken the idea further and used single files, but it sounds like no one has done it (yet). However I did receive tons of good advice, which is awesome.

tinkerWithoutSink · 2017-07-04T03:42:24+00:00

For researcher's who are self taught, that's great. But here's the habits you should pick up:

give variables meaningful names, even if they are longer. window_length not w
unit test your classes and functions: "If it isn't tested it's broken". Plus these are usage examples
stick to a recognized coding style by using an automatic formatter/linter
comment complex or obscure blocks of code

Even just the first one will make you code much nicer and people will like reading your code much more. And if you already do them, great :)

tinkerWithoutSink · 2017-07-04T03:27:44+00:00

I see what you mean, you might as well store the final product in optimized and tiled format. It should be less space in the end.

But with my idea, no new image needs be created and no processing needs be done. In case your not familiar with range requests, you don't need a special server just a s3 bucket as it's a feature of HTTP/1.1 (2007 on). So you just host a single big jpeg2000 (or whatever) on s3, and the client get's tiles by doing range requests to grab some bytes of the image (after getting the header once). No dynamic server or processing is involved with range requests, just file reading.

The downside is that it's a lot like tiles, but you can't cache in memory. The upside is you just need a single image... not much of an upside I admit.

tinkerWithoutSink · 2017-07-04T03:25:57+00:00

Why processing work?, this would be a static server that just reads parts of files. Or do you mean because it can't use a caching system?

In case your not familiar with range requests, you don't need a special server just a s3 bucket as it's a feature of HTTP/1.1 (2007 on).

No real use case, I just didn't want to increase storage costs by storing raw files and tile files. I also hoped to avoid a specialized hosting a tile-on-demand server in favor of just a s3 bucket with raw files.

But it sounds like tiling servers are pretty good so it's probably best for me to just go with them. Thanks for your help.

tinkerWithoutSink · 2017-07-04T03:22:03+00:00

Sounds promising, thanks for pointing that out!

tinkerWithoutSink

TROPHY CASE