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Minimal algorithmic information loss methods for dimension reduction, feature selection and network sparsification
We present a novel, domain-agnostic, model-independent, unsupervised, and universally
applicable approach for data summarization. Specifically, we focus on addressing the …
applicable approach for data summarization. Specifically, we focus on addressing the …
[HTML][HTML] Algorithmic information distortions in node-aligned and node-unaligned multidimensional networks
In this article, we investigate limitations of importing methods based on algorithmic
information theory from monoplex networks into multidimensional networks (such as …
information theory from monoplex networks into multidimensional networks (such as …
An Algorithmic Information Distortion in Multidimensional Networks
Network complexity, network information content analysis, and lossless compressibility of
graph representations have been played an important role in network analysis and network …
graph representations have been played an important role in network analysis and network …
Transtemporal edges and crosslayer edges in incompressible high-order networks
This work presents some outcomes of a theoretical investigation of incompressible high-
order networks defined by a generalized graph representation. We study some of their …
order networks defined by a generalized graph representation. We study some of their …
On the existence of hidden machines in computational time hierarchies
Challenging the standard notion of totality in computable functions, one has that, given any
sufficiently expressive formal axiomatic system, there are total functions that, although …
sufficiently expressive formal axiomatic system, there are total functions that, although …