138 citations · 771 across the 19 of their papers we have counts for
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cs.LG2023★ 24 cited
A survey and taxonomy of loss functions in machine learning
Lorenzo Ciampiconi, Adam Elwood, Marco Leonardi +2
Most state-of-the-art machine learning techniques revolve around the optimisation of loss functions. Defining appropriate loss functions is therefore critical to successfully solvi…
cs.LG2022★ 1 cited
Maximum entropy exploration in contextual bandits with neural networks and energy based models
Adam Elwood, Marco Leonardi, Ashraf Mohamed +1
Contextual bandits can solve a huge range of real-world problems. However, current popular algorithms to solve them either rely on linear models, or unreliable uncertainty estimati…