Kernel Fisher Discriminant Analysis
In statistics, kernel Fisher discriminant analysis (KFD), also known as generalized discriminant analysis and kernel discriminant analysis, is a kernelized version of linear discriminant analysis. It is named after Ronald Fisher. Using the kernel trick, LDA is implicitly performed in a new feature space, which allows non-linear mappings to be learned.
“Linear Discriminant Analysis”
Kernel Fisher Discriminant Analysis (KFD,KFDA) google
Multi-Advisor Reinforcement Learning
This article deals with a novel branch of Separation of Concerns, called Multi-Advisor Reinforcement Learning (MAd-RL), where a single-agent RL problem is distributed to $n$ learners, called advisors. Each advisor tries to solve the problem with a different focus. Their advice is then communicated to an aggregator, which is in control of the system. For the local training, three off-policy bootstrapping methods are proposed and analysed: local-max bootstraps with the local greedy action, rand-policy bootstraps with respect to the random policy, and agg-policy bootstraps with respect to the aggregator’s greedy policy. MAd-RL is positioned as a generalisation of Reinforcement Learning with Ensemble methods. An experiment is held on a simplified version of the Ms. Pac-Man Atari game. The results confirm the theoretical relative strengths and weaknesses of each method. … Multi-Advisor Reinforcement Learning google
Neural Networks / Artificial Neural Networks
In computer science and related fields, artificial neural networks (ANNs) are computational models inspired by an animal’s central nervous systems (in particular the brain) which is capable of machine learning as well as pattern recognition. Artificial neural networks are generally presented as systems of interconnected “neurons” which can compute values from inputs. … Neural Networks / Artificial Neural Networks (ANN) google