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Gamal
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Quantitative methods in magic

March 6th, 2018, 11:28 am

Applications of maths and computers in magic are still undervalued. To start with https://arxiv.org/abs/1709.03803
 
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ISayMoo
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Re: Quantitative methods in magic

March 8th, 2018, 10:33 pm

I've seen this paper. One of the worst ever.
 
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tags
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Re: Quantitative methods in magic

March 9th, 2018, 8:22 am

11 authors, several universities involved, and this research was funded.
 
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Gamal
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Re: Quantitative methods in magic

March 9th, 2018, 8:41 am

Magic
 
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Cuchulainn
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Re: Quantitative methods in magic

March 9th, 2018, 11:24 am

N(N-1)/2 communication channels!

N = 11 => 55. Who are the silent partners?


Image
 
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ISayMoo
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Re: Quantitative methods in magic

March 11th, 2018, 12:17 am

11 authors, several universities involved, and this research was funded.
I've recently listened to a talk by a post-doc from Queen Mary University in London. She was optimising the random seed of the PRNG used by her model as a hyper-parameter, showing plots of reward function for "good seeds" and "bad seeds". To her credit, she did say "some people may find it controversial".
 
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Traden4Alpha
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Joined: September 20th, 2002, 8:30 pm

Re: Quantitative methods in magic

March 11th, 2018, 12:24 am

11 authors, several universities involved, and this research was funded.
I've recently listened to a talk by a post-doc from Queen Mary University in London. She was optimising the random seed of the PRNG used by her model as a hyper-parameter, showing plots of reward function for "good seeds" and "bad seeds". To her credit, she did say "some people may find it controversial".
LOL!

Just wait until some AI finds the "good seed" that exactly outputs the "random" movements of the stock market.

Douglas Adams knew the Earth was just a giant computer. Ergo the market is really a PRNG.
 
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ISayMoo
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Re: Quantitative methods in magic

March 11th, 2018, 12:27 am

I briefly wondered once if various Deep Learning models which require random inputs (e.g. autoencoders) could learn to predict the next random value generated, thus "cheating". But I doubt it's possible without a humongous training sample and large model capacity.
 
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Traden4Alpha
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Re: Quantitative methods in magic

March 11th, 2018, 1:02 am

Yes, the bit depth of the hidden state of the better PRNGs does seem to imply a humongous training sample.

However, for many numerical PRNG applications, even a volatile estimate of MSBs would be quite meaningful.

For cryptocurrencies, anything that helps predict outputs overlapping with the nonce would boost mining efficiency.

And for cryptography, perhaps sparse bit prediction would enable enough extraction of meaning to decode low entropy plain text.

(The deeper issue is: if Deep Learning models reach this level of sophistication, will they have the sophistication to withhold information on their results???)
 
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SWilson
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Re: Quantitative methods in magic

March 12th, 2018, 10:30 pm

What about amplitude and vector quantization......
 
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Cuchulainn
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Re: Quantitative methods in magic

March 12th, 2018, 11:07 pm

11 authors, several universities involved, and this research was funded.
I've recently listened to a talk by a post-doc from Queen Mary University in London. She was optimising the random seed of the PRNG used by her model as a hyper-parameter, showing plots of reward function for "good seeds" and "bad seeds". To her credit, she did say "some people may find it controversial".
Image
 
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Traden4Alpha
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Joined: September 20th, 2002, 8:30 pm

Re: Quantitative methods in magic

March 12th, 2018, 11:20 pm

11 authors, several universities involved, and this research was funded.
I've recently listened to a talk by a post-doc from Queen Mary University in London. She was optimising the random seed of the PRNG used by her model as a hyper-parameter, showing plots of reward function for "good seeds" and "bad seeds". To her credit, she did say "some people may find it controversial".
Image
Falsehoods also pass through the same three stages. Some even come out of stage 3 stronger than ever.
 
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mtsm
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Re: Quantitative methods in magic

March 13th, 2018, 12:54 am

Applications of maths and computers in magic are still undervalued. To start with https://arxiv.org/abs/1709.03803
Why do you think it's so bad? do you mean the execution of the authors is bad or do you mean the whole approach is just idiotic?
 
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Gamal
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Re: Quantitative methods in magic

March 13th, 2018, 9:18 am

Not the paper itself but the subject. What we did in the 90-ties and then had some methodological background, we were able to explain in a few words why and what. Their approach is closer to what astrologists did a few hundred years back - some unjustified operations on numbers with nonclear conclusions which could be the opposite. Back to olde good times of magic, ladies and gentlemen.
 
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katastrofa
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Re: Quantitative methods in magic

March 13th, 2018, 6:27 pm

I briefly wondered once if various Deep Learning models which require random inputs (e.g. autoencoders) could learn to predict the next random value generated, thus "cheating". But I doubt it's possible without a humongous training sample and large model capacity.
They could guess the PRNG's seed state based on several numbers. Learning to hack :-) But you do use cryptographically secure PRNGs, don't you.