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Analysing the Effects of Transfer Learning on Low-Resourced Named Entity Recognition Performance
Transfer learning has led to large gains in performance for nearly all NLP tasks while making downstream models easier and faster to …
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Effect of Tokenisation Strategies for Low-Resourced Southern African Languages
Research into machine translation for African languages is very limited and low- resourced in terms of datasets and model evaluations. …
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Generalisation in Lifelong Reinforcement Learning through Logical Composition
We leverage logical composition in reinforcement learning to create a framework that enables an agent to autonomously determine whether …
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The Challenge of Redundancy on Multi-Agent Value Factorisation
Recently there has been great development in the field of multi-agent reinforcement learning (MARL). In the cooperative partially …
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Should I Trust You? Incorporating Unreliable Expert Advice in Human-Agent Interaction
A major concern in reinforcement learning, especially as it is applied to real-world and robotics problems, is that of …
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Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization
Training sparse networks to converge to the same performance as dense neural architectures has proven to be elusive. Recent work …
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Logical Composition for Lifelong Reinforcement Learning
The ability to produce novel behaviours from existing skills is an important property of lifelong-learning agents. We build on recent …
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Learning Object-Centric Representations for High-Level Planning in Minecraft
We propose a method for autonomously learning an object-centric representation of a highdimensional environment that is suitable for …
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A Boolean Task Algebra for Reinforcement Learning
We propose a framework for defining a Boolean algebra over the space of tasks. This allows us to formulate new tasks in terms of the …
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Learning to Plan with Portable Symbols
We present a framework for autonomously learning a portable symbolic representation that describes a collection of low-level continuous …
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