From: Saku Laesvuori <saku@laesvuori.fi>
To: Nathan Dehnel <ncdehnel@gmail.com>
Cc: guix-devel@gnu.org
Subject: Re: Binary descriptors for OpenCV
Date: Tue, 1 Aug 2023 23:37:00 +0300 [thread overview]
Message-ID: <20230801203700.67ef6l3ibg27wzpk@X-kone> (raw)
In-Reply-To: <CAEEhgEuqL8P6y5OPBAbe5nZsxaKqAe3G+gQzMj0w_ixfqx5rhw@mail.gmail.com>
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> Is this even practically possible? How do you re-train a blob you know
> nothing about? To me this sounds similar to saying a compiled binary
> is free software if the license allows you to decompile it and
> deobfuscate it.
If you know how to convert the blob to weights in the neural network
(something the program has to do to make any use of the blob) and know
the error function, you can continue the training with new data.
This is not any different from training the model from scratch. In both
cases we begin with some set of initial weights for a huge polynomial,
take a sample of our training data, compute the polynomial for it and
tweak the weights a bit if the result was not what we wanted. The only
difference is that when training from scratch we begin with very bad
guesses for all the weights. When we are tuning the blob we begin with
much better guesses that are closer to the values we would actually
want.
The difference to a compiled binary program is that you would want to
edit it in the source code form. You really would not want to edit the
neural network by editing the original training data and retraining the
entire network from scratch. The data set probably contains thousands,
tens of thousands or even more random pictures that you would have to go
through and see if they represent the data and results you want. It
would be much easier to test whether the network gives the correct
results and train it with new data that you know describes your problem
better.
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next prev parent reply other threads:[~2023-08-01 20:37 UTC|newest]
Thread overview: 17+ messages / expand[flat|nested] mbox.gz Atom feed top
2023-08-01 18:50 Binary descriptors for OpenCV Nathan Dehnel
2023-08-01 20:37 ` Saku Laesvuori [this message]
2023-08-01 20:58 ` Nathan Dehnel
2023-08-02 4:46 ` Saku Laesvuori
2023-08-02 20:25 ` Nathan Dehnel
2023-08-03 6:18 ` Saku Laesvuori
-- strict thread matches above, loose matches on Subject: below --
2023-08-01 7:21 Nathan Dehnel
2023-08-01 12:14 ` Ricardo Wurmus
2023-08-16 16:55 ` Ludovic Courtès
2023-08-17 21:57 ` Nathan Dehnel
2023-08-17 23:18 ` Maxim Cournoyer
2023-08-24 15:08 ` Ludovic Courtès
2023-07-31 13:12 Ricardo Wurmus
2023-08-01 14:02 ` Maxim Cournoyer
2023-08-01 14:39 ` Saku Laesvuori
2023-08-19 9:37 ` Simon Tournier
2023-08-24 15:06 ` Ludovic Courtès
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