Viewing profile — bowlesbe
bowlesbe
HN member- Joined
- Sat, Nov 19, 2016, 12:16 AM UTC
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About bowlesbe
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Recent public activity
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Comment #12995296
Could you elaborate? I'm not sure if I follow
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Comment #12995290
haha, absolutely. It takes a lot of intelligence to detect non-informativeness. you might enjoy: http://journal.sjdm.org/15/15923a/jdm15923a.pdf
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Comment #12995265
Are you sure about the padding? On page 1746, bottom right it says "padded as necessary". And intuitively it makes sense that all your inputs need to be the same size for a CNN.
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Comment #12995251
This is a great point, would be worth further investigation. And I agree with your general interpretation. It would be interesting to look further at where CNN is failing to detect…
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Comment #12995228
I think deep learning can be seen as a class of machine learning techniques with more flexibility and which uses neural networks (usually with quite a few layers).
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Comment #12995224
I appreciate this!
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Comment #12995217
This is actually a great point. Thanks for sharing. I should maybe considering removing LIME in that context or changing the wording.
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Comment #12995185
Thanks, would you mind expanding? I also played around with some char CNNs. They had similar performance.
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Comment #12992174
50K is not that tiny, but I'd say in the hundreds is pretty small. I'd say hundreds of training examples is pretty normal in academia, but typically quite small in industry, partic…
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Comment #12992163
I would agree. Its kind of amazing that it indeed it does seem to work better than simpler models.
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Comment #12992157
This is really great idea. Actually if there is something you can share along these lines, that would be amazing. I know Crowd Flower has a great "internal only" tool, which is kin…
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Comment #12992142
Thanks! I'll check it out. I have also been reading about abstractive summarization - hard problem it seems!
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Comment #12991438
Great question and I share your intuition but I think its all properly regularizing your model. I guess for neural networks, Dropout works really darn well as a regularization stra…
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Comment #12991134
This is correct. We had 300-400 examples of each
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Comment #12991130
Great point! I considering using fasttext as a baseline, however in practice fasttext really didn't work well at all with the small data set, much worse than the tfidf baseline. I …
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Comment #12991122
Thanks for the comment! There were a few hundred sentences of each, collected internally from from a wide number of descriptions. Yes, I'd definitely agree- more data is what we ne…