4 citations · 8 across the 9 of their papers we have counts for
9 papers
Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation
Alexander Long, Alan Blair, Herke van Hoof
We present Nonparametric Approximation of Inter-Trace returns (NAIT), a Reinforcement Learning algorithm for discrete action, pixel-based environments that is both highly sample an…
Man versus Machine: AutoML and Human Experts' Role in Phishing Detection
Rizka Purwanto, Arindam Pal, Alan Blair +1
Machine learning (ML) has developed rapidly in the past few years and has successfully been utilized for a broad range of tasks, including phishing detection. However, building an…
Epigenetic evolution of deep convolutional models
Alexander Hadjiivanov, Alan Blair
In this study, we build upon a previously proposed neuroevolution framework to evolve deep convolutional models. Specifically, the genome encoding and the crossover operator are ex…
Eccentric Regularization: Minimizing Hyperspherical Energy without explicit projection
Xuefeng Li, Alan Blair
Several regularization methods have recently been introduced which force the latent activations of an autoencoder or deep neural network to conform to either a Gaussian or hypersph…
Simeon -- Secure Federated Machine Learning Through Iterative Filtering
Nicholas Malecki, Hye-young Paik, Aleksandar Ignjatovic +2
Federated learning enables a global machine learning model to be trained collaboratively by distributed, mutually non-trusting learning agents who desire to maintain the privacy of…
Complexity-based speciation and genotype representation for neuroevolution
Alexander Hadjiivanov, Alan Blair
This paper introduces a speciation principle for neuroevolution where evolving networks are grouped into species based on the number of hidden neurons, which is indicative of the c…