2 citations · 4 across the 5 of their papers we have counts for
9 papers · 1 filter
Controllability, Multiplexing, and Transfer Learning in Networks using Evolutionary Learning
Rise Ooi, Chao-Han Huck Yang, Pin-Yu Chen +5
Networks are fundamental building blocks for representing data, and computations. Remarkable progress in learning in structurally defined (shallow or deep) networks has recently be…
Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model
C. -H. Huck Yang, Fangyu Liu, Jia-Hong Huang +6
Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. Based on the fact that fun…
A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases
C. -H. Huck Yang, Jia-Hong Huang, Fangyu Liu +5
Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. We propose a novel visual-…
The Thermodynamics of Network Coding, and an Algorithmic Refinement of the Principle of Maximum Entropy
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
The principle of maximum entropy (Maxent) is often used to obtain prior probability distributions as a method to obtain a Gibbs measure under some restriction giving the probabilit…
Algorithmic Complexity and Reprogrammability of Chemical Structure Networks
Hector Zenil, Narsis A. Kiani, Ming-Mei Shang +1
Here we address the challenge of profiling causal properties and tracking the transformation of chemical compounds from an algorithmic perspective. We explore the potential of appl…
Symmetry and Algorithmic Complexity of Polyominoes and Polyhedral Graphs
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
We introduce a definition of algorithmic symmetry able to capture essential aspects of geometric symmetry. We review, study and apply a method for approximating the algorithmic com…