no code implementations • 21 Nov 2022 • Joshua Lockhart, Daniele Magazzeni, Manuela Veloso
The Concept Bottleneck Models (CBMs) of Koh et al. [2020] provide a means to ensure that a neural network based classifier bases its predictions solely on human understandable concepts.
no code implementations • 7 Nov 2022 • Joshua Lockhart, Nicolas Marchesotti, Daniele Magazzeni, Manuela Veloso
Concept bottleneck models perform classification by first predicting which of a list of human provided concepts are true about a datapoint.
no code implementations • 5 Oct 2022 • Mattia Villani, Joshua Lockhart, Daniele Magazzeni
Feature importance techniques have enjoyed widespread attention in the explainable AI literature as a means of determining how trained machine learning models make their predictions.
no code implementations • 15 May 2022 • Thomas Spooner, Rui Silva, Joshua Lockhart, Jason Long, Vacslav Glukhov
Solving general Markov decision processes (MDPs) is a computationally hard problem.
no code implementations • 23 Mar 2022 • Tiffany Tuor, Joshua Lockhart, Daniele Magazzeni
Our proposed approach enhances conventional federated learning techniques to make them suitable for this asynchronous training in this intra-organisation, cross-silo setting.
no code implementations • 12 Oct 2020 • Joshua Lockhart, Samuel Assefa, Ayham Alajdad, Andrew Alexander, Tucker Balch, Manuela Veloso
We show that conventional crowdsourcing algorithms struggle in this user feedback setting, and present a new algorithm, SURF, that can cope with this non-response ambiguity.
no code implementations • 27 Apr 2020 • Joshua Lockhart, Samuel Assefa, Tucker Balch, Manuela Veloso
Document classification is ubiquitous in a business setting, but often the end users of a classifier are engaged in an ongoing feedback-retrain loop with the team that maintain it.
no code implementations • 28 Nov 2019 • Mahmoud Mahfouz, Angelos Filos, Cyrine Chtourou, Joshua Lockhart, Samuel Assefa, Manuela Veloso, Danilo Mandic, Tucker Balch
The dynamics of financial markets are driven by the interactions between participants, as well as the trading mechanisms and regulatory frameworks that govern these interactions.
no code implementations • 10 Apr 2018 • Edward Grant, Marcello Benedetti, Shuxiang Cao, Andrew Hallam, Joshua Lockhart, Vid Stojevic, Andrew G. Green, Simone Severini
Quantum circuits with hierarchical structure have been used to perform binary classification of classical data encoded in a quantum state.
Quantum Physics