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05/18/2023
A Parameter-Efficient Learning Approach to Arabic Dialect Identification with Pre-Trained General-Purpose Speech Model
In this work, we explore Parameter-Efficient-Learning (PEL) techniques t...
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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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02/03/2020
Evolving Neural Networks through a Reverse Encoding Tree
NeuroEvolution is one of the most competitive evolutionary learning fram...
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10/07/2019
Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces
We show how complexity theory can be introduced in machine learning to h...
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05/18/2018
An Algorithmic Refinement of Maxent Induces a Thermodynamic-like Behaviour in the Reprogrammability of Generative Mechanisms
Reprogramming a generative mechanism to produce a different object is as...
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02/24/2018
Symmetry and Algorithmic Complexity of Polyominoes and Polyhedral Graphs
We introduce a definition of algorithmic symmetry able to capture essent...
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02/18/2018
Ab initio Algorithmic Causal Deconvolution of Intertwined Programs and Networks by Generative Mechanism
To extract and learn representations leading to generative mechanisms fr...
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02/18/2018
Algorithmic Information Dynamics of Persistent Patterns and Colliding Particles in the Game of Life
We demonstrate the way to apply and exploit the concept of algorithmic i...
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02/16/2018
Algorithmic Complexity and Reprogrammability of Chemical Structure Networks
Here we address the challenge of profiling causal properties and trackin...
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02/16/2018
Parameter-free Network Sparsification and Data Reduction by Minimal Algorithmic Information Loss
The study of large and complex datasets, or big data, organized as netwo...
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09/01/2017
