Two experiments were carried out to investigate how Algorithmic Specified Complexity (ASC) might serve as a tool, specifically in the area of classification AI, and how well the theory around it predicts the characteristics of random numbers. One evaluated an approach to measuring ASC in pictures by how well it helped in classification, and the other compared predictions and observations of the compressibility of random bitstrings. The ASC of MNIST pictures was estimated by saving concatenations of samples as PNG. The expected ASC of random bitstrings was compared to average observed ASC (OASC) values from LZ78 Huffman codes. Observed ASC of MNIST pictures helped to identify them, and as predicted, expectations of ASC were higher than those...
We show that real-value approximations of Kolmogorov-Chaitin (Km) using the algorithmic Coding theor...
Given the widespread use of lossless compression algorithms to approximate algorithmic (Kolmogorov-C...
What is the relationship between the complexity of a learner<br />and the randomness of his mi...
We propose a test based on the theory of algorithmic complexity and an experimental evaluation of Le...
Abstract—An event with low probability is unlikely to happen, but events with low probability happen...
Algorithmic complexity provides a mathematical formal notion of string complexity. Building on this,...
We investigate the properties of a Block Decomposition Method (BDM), which extends the power of a Co...
We propose a measure based upon the fundamental theoretical concept in algorithmic information theor...
We discuss basic sample complexity theory and it's impact on classification success evaluation,...
Although information content is invariant up to an additive constant, the range of possible additive...
This paper focuses on a general setup for obtaining sample size lower bounds for learning concept cl...
The standard language for describing the asymptotic behavior of algorithms is theoretical computatio...
This is a presentation about joint work between Hector Zenil and Jean-Paul Delahaye. Zenil presents ...
What is &quot;randomness&quot;? The LZ76 paper explores the randomness of sequences. One exp...
In this study, we develop a technique to measure randomness and complexity for various systems. The ...
We show that real-value approximations of Kolmogorov-Chaitin (Km) using the algorithmic Coding theor...
Given the widespread use of lossless compression algorithms to approximate algorithmic (Kolmogorov-C...
What is the relationship between the complexity of a learner<br />and the randomness of his mi...
We propose a test based on the theory of algorithmic complexity and an experimental evaluation of Le...
Abstract—An event with low probability is unlikely to happen, but events with low probability happen...
Algorithmic complexity provides a mathematical formal notion of string complexity. Building on this,...
We investigate the properties of a Block Decomposition Method (BDM), which extends the power of a Co...
We propose a measure based upon the fundamental theoretical concept in algorithmic information theor...
We discuss basic sample complexity theory and it's impact on classification success evaluation,...
Although information content is invariant up to an additive constant, the range of possible additive...
This paper focuses on a general setup for obtaining sample size lower bounds for learning concept cl...
The standard language for describing the asymptotic behavior of algorithms is theoretical computatio...
This is a presentation about joint work between Hector Zenil and Jean-Paul Delahaye. Zenil presents ...
What is &quot;randomness&quot;? The LZ76 paper explores the randomness of sequences. One exp...
In this study, we develop a technique to measure randomness and complexity for various systems. The ...
We show that real-value approximations of Kolmogorov-Chaitin (Km) using the algorithmic Coding theor...
Given the widespread use of lossless compression algorithms to approximate algorithmic (Kolmogorov-C...
What is the relationship between the complexity of a learner<br />and the randomness of his mi...