Viewing profile — dhammack
dhammack
HN member- Joined
- Sat, Feb 18, 2012, 8:55 PM UTC
- HN karma
- 196
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- 57 items
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About dhammack
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Recent public activity
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Comment #40104874
Was this summary generated by a LLM?
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Comment #35730753
On the broader point though, there certainly are some companies that have access to unique datasets that they can take advantage of. Meta and Google come to mind as obvious ones, p…
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Comment #34175964
Had a similar experience in middle school. We started initially doing net-send to specific users and having played around a little bit with batch files/command prompt before I trie…
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Comment #28545073
You can get the real content without the commentary at https://www.volcanodiscovery.com/lapalma/sep2021seismic-cris... Also see https://en.wikipedia.org/wiki/Cumbre_Vieja_tsunami_h…
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Comment #25417085
Thanks for posting. In the early 2000's me, my brothers, and my dad spent several months taking pictures and submitting each sequential minute between 8-9. Looking back probably 20…
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Comment #19521429
Looks like only scoring code, not training :(
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Comment #19056434
Voloridge Investment Management | Quant Analyst | Jupiter, FL | Full-time | ONSITE Voloridge Investment Management is an SEC registered investment advisor that implements bleeding …
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Comment #18465926
Hey I'm not familiar with this way of comparing classical and quantum computation. Can you point me to some more details? I have Nielson's book but don't remember seeing this analo…
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Comment #12457578
I see. I still think it's easier to apply deepmind's feature transform on text rather than to try to invert a neural network. Armed with a network trained on Trump, deepmind's feat…
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Comment #12457062
It seems like you're using WaveNet to do speech-to-text when we have better tools for that. To transfer text from Trump to Clinton, first run speech-to-text on Trump speech and the…
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Comment #11328225
My hypothesis is that all RNNs (and in general complex dynamical systems) need to be reset periodically. If run for too long without resetting, they tend to get stuck in strange st…
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Comment #9961673
It just finished, I got 4th. I used convnets. With the correct initialization and data preprocessing they actually are quite easy to train.
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Comment #9354190
The other thing hedge funds offer is alternative markets to track. So while some may track the U.S. stock market (which you can get by just buying SPY), some funds track other mark…
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Comment #9080520
If you think the true sentiment is symmetric, you can just change the decision threshold so that your algorithm answers positively about half the time. Just say positive when the s…
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Comment #9034246
You also may want to try betting on the spread between male-only companies and ones with at least one woman on the board. If the investment thesis is sound (board gender diversity …
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Comment #8593919
#4 is the only one which I would say does not hold. I'd be very surprised if a firm of manual traders could consistently outperform the market (or beat a Sharpe of 1).
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Comment #8577788
FYI - Hinton is doing an AMA on r/machinelearning on Monday!
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Comment #8130045
Very impressive! Some cool ones it recognized: milk jug http://cdn-jpg.allyou.com/sites/default/files/image/2014/01/... ["milk", "gallon", "jug", "product", "detergent", "plastic",…
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Comment #8104669
I think it's rescaling all images to fit the training size. If that is the case, then when your image has very different dimensions it gets distorted and confused. Try something wi…
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Comment #6967277
Your argument is more philosophical than mathematical. Lines are traditionally defined as the set of all points which satisfy some critera. In this case, a line is precisely made u…
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Comment #6875882
Can you imagine the datasets FB has to work with? Statuses, pictures, locations, social graphs. It's incredible. It's hard to blame LeCun/Hinton/Ng for moving towards industry with…
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Comment #6867315
I like to think of the vectorized representation as just a nonlinear transformation to a higher dimensional space with a classifier afterwords. If you're familiar with linear algeb…
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Comment #6867110
I've managed to get an intuition for backpropagation (the way gradients are computed for neural networks) using a similar analogy. The basic idea is that it's just a signal moving …