43 citations · 126 across the 29 of their papers we have counts for
4 papers · 1 filter
Learning Options from Demonstration using Skill Segmentation
Matthew Cockcroft, Shahil Mawjee, Steven James +1
We present a method for learning options from segmented demonstration trajectories. The trajectories are first segmented into skills using nonparametric Bayesian clustering and a r…
Quantisation and Pruning for Neural Network Compression and Regularisation
Kimessha Paupamah, Steven James, Richard Klein
Deep neural networks are typically too computationally expensive to run in real-time on consumer-grade hardware and low-powered devices. In this paper, we investigate reducing the…
Inter- and Intra-domain Knowledge Transfer for Related Tasks in Deep Character Recognition
Nishai Kooverjee, Steven James, Terence van Zyl
Pre-training a deep neural network on the ImageNet dataset is a common practice for training deep learning models, and generally yields improved performance and faster training tim…
A Boolean Task Algebra for Reinforcement Learning
Geraud Nangue Tasse, Steven James, Benjamin Rosman
The ability to compose learned skills to solve new tasks is an important property of lifelong-learning agents. In this work, we formalise the logical composition of tasks as a Bool…