research
∙
06/02/2023
Modularity based linkage model for neuroevolution
Crossover between neural networks is considered disruptive due to the st...
share
research
∙
05/17/2023
Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCS
Interest in reinforcement learning (RL) has recently surged due to the a...
research
∙
05/17/2023
A Genetic Fuzzy System for Interpretable and Parsimonious Reinforcement Learning Policies
Reinforcement learning (RL) is experiencing a resurgence in research int...
research
∙
05/13/2022
Modularity in NEAT Reinforcement Learning Networks
Modularity is essential to many well-performing structured systems, as i...
research
∙
04/08/2022
Approximate discounting-free policy evaluation from transient and recurrent states
In order to distinguish policies that prescribe good from bad actions in...
research
∙
01/19/2022
Graph Neural Network-based Android Malware Classification with Jumping Knowledge
This paper presents a new Android malware detection method based on Grap...
research
∙
09/30/2021
From Zero-Shot Machine Learning to Zero-Day Attack Detection
The standard ML methodology assumes that the test samples are derived fr...
research
∙
08/28/2021
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks
The tremendous numbers of network security breaches that have occurred i...
research
∙
07/03/2021
Examining average and discounted reward optimality criteria in reinforcement learning
In reinforcement learning (RL), the goal is to obtain an optimal policy,...
research
∙
05/28/2021
A nearly Blackwell-optimal policy gradient method
For continuing environments, reinforcement learning methods commonly max...
research
∙
04/19/2021
Benchmarking the Benchmark – Analysis of Synthetic NIDS Datasets
Network Intrusion Detection Systems (NIDSs) are an increasingly importan...
research
∙
03/30/2021
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System
This paper presents a new network intrusion detection system (NIDS) base...
research
∙
10/18/2020
Average-reward model-free reinforcement learning: a systematic review and literature mapping
Model-free reinforcement learning (RL) has been an active area of resear...
research
∙
09/03/2020
Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
Learning classifier systems (LCSs) are population-based predictive syste...
research
∙
02/20/2020
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks
Analysing and computing with Gaussian processes arising from infinitely ...
research
∙
11/29/2019
Richer priors for infinitely wide multi-layer perceptrons
It is well-known that the distribution over functions induced through a ...
research
∙
10/19/2018
Exchangeability and Kernel Invariance in Trained MLPs
In the analysis of machine learning models, it is often convenient to as...
research
∙
11/24/2017
Invariance of Weight Distributions in Rectified MLPs
An interesting approach to analyzing and developing tools for neural net...
research
∙
11/27/2015
