2 papers
cs.IT2026
Tighter Bounds for Algorithmic Complexity Estimation Using a Reusable Code-Based Block Decomposition Method
Eduardo Yuji Sakabe, Felipe S. Abrahão, Santiago Hernández-Orozco +2
The Block Decomposition Method (BDM) was introduced as an alternative to popular lossless compression methods such as LZW for estimating algorithmic complexity from the principles…
cs.LG2025
Binarized Neural Networks Converge Toward Algorithmic Simplicity: Empirical Support for the Learning-as-Compression Hypothesis
Eduardo Y. Sakabe, Felipe S. Abrahão, Alexandre Simões +4
Understanding and controlling the informational complexity of neural networks is a central challenge in machine learning, with implications for generalization, optimization, and mo…