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9
Just-in-Time Sparsity: Learning Dynamic Sparsity Schedules
Sparse neural networks have various computational benefits while often being able to maintain or improve the generalization performance …
Kale-ab Tessera
,
Chiratidzo Matowe
,
Arnu Pretorius
,
Benjamin Rosman
,
Sara Hooker
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World Value Functions: Knowledge Representation for Learning and Planning
We propose world value functions (WVFs), a type of goaloriented general value function that represents how to solve not just a given …
Geraud Nangue Tasse
,
Benjamin Rosman
,
Steven James
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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 …
Michael Beukman
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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. …
Jenalea Rajab
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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 …
Geraud Nangue Tasse
,
Steven James
,
Benjamin Rosman
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Project
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 …
Siddarth Singh
,
Benjamin Rosman
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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 …
Tamlin Love
,
Ritesh Ajoodha
,
Benjamin Rosman
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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 …
Kale-ab Tessera
,
Sara Hooker
,
Benjamin Rosman
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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 …
Geraud Nangue Tasse
,
Steven James
,
Benjamin Rosman
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Project
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 …
Steven James
,
Benjamin Rosman
,
George Konidaris
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