Re: ANN: Dogelog Player 1.2.6 (Segmented Fileaccess)

An autoencoder learns two functions: an encoding
function that transforms the input data, and a
decoding function that recreates the input data
from the encoded representation. We approach
autoencoders via our already developed SAT Learning
in the Prolog programming language.
Switching from a marginal maximizer to a conditional
maximizer gives better results but also requires a
more costly and slower optimizer. Maximum entropy
methods were already suggest by Peter Cheeseman in
1987. Mostlikely flawed since there is not yet a
feedback loop from the decoder to the encoder.
Maximum Entropy in SAT Autoencoding
https://x.com/dogelogch/status/1890093860782764409
Maximum Entropy in SAT Autoencoding
https://www.facebook.com/groups/dogelog
Mild Shock schrieb:

 Dogelog Player is a Prolog system for JavaScript,
Python and Java. It is 100% written in Prolog itself.
We present an enhancement to DCG translation. It uses
unification spilling to reduce the number of needed
unify (=)/2 calls and intermediate variables.
 Unification spilling can be readily implemented by
performing unification (=)/2 during DCG translation.
Careful spilling without breaking steadfastness gave
us a 10% — 25% speed increase not only for the calculator
example but also for the Albufeira transpiler.
 See also:
 DCG Translation with Unification Spilling
https://x.com/dogelogch/status/1889270444647182542
 DCG Translation with Unification Spilling
https://www.facebook.com/groups/dogelog