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04/21/2023
The simplicity bubble effect as a zemblanitous phenomenon in learning systems
The ubiquity of Big Data and machine learning in society evinces the nee...
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03/28/2023
Optimal Spatial Deconvolution and Message Reconstruction from a Large Generative Model of Models
We introduce a general-purpose univariate signal deconvolution method ba...
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09/30/2022
On the Salient Limitations of the Methods of Assembly Theory and their Classification of Molecular Biosignatures
A recently introduced approach termed "Assembly Theory", featuring a com...
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12/22/2021
Algorithmic Probability of Large Datasets and the Simplicity Bubble Problem in Machine Learning
When mining large datasets in order to predict new data, limitations of ...
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05/31/2021
Emergence and algorithmic information dynamics of systems and observers
Previous work has shown that perturbation analysis in software space can...
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09/23/2020
Emergence of complex data from simple local rules in a network game
As one of the main subjects of investigation in data science, network sc...
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09/12/2020
An Algorithmic Information Distortion in Multidimensional Networks
Network complexity, network information content analysis, and lossless c...
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09/02/2020
On the existence of hidden machines in computational time hierarchies
Challenging the standard notion of totality in computable functions, one...
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05/13/2019
Transtemporal edges and crosslayer edges in incompressible high-order networks
This work presents some outcomes of a theoretical investigation of incom...
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04/08/2019
Learning the undecidable from networked systems
This article presents a theoretical investigation of computation beyond ...
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12/04/2018
On incompressible high order networks
This work presents a theoretical investigation of incompressible high or...
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10/27/2018