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09/08/2023
Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse
Counterfactuals operationalised through algorithmic recourse have become...
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08/31/2023
Strategies for engaging clinical participants in the co-design of software for healthcare domains
Co-design is an effective method for designing software, but implementin...
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05/20/2023
Privacy in Multimodal Federated Human Activity Recognition
Human Activity Recognition (HAR) training data is often privacy-sensitiv...
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05/19/2023
MIDI-Draw: Sketching to Control Melody Generation
We describe a proof-of-principle implementation of a system for drawing ...
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05/19/2023
What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics
In this study, we investigate the feasibility of utilizing state-of-the-...
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03/17/2023
Disentangling the Link Between Image Statistics and Human Perception
In the 1950s Horace Barlow and Fred Attneave suggested a connection betw...
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02/10/2023
Two-step counterfactual generation for OOD examples
Two fundamental requirements for the deployment of machine learning mode...
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02/06/2023
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations
In supervised learning, low quality annotations lead to poorly performin...
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01/31/2023
Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease
Early diagnosis of Alzheimer's disease (AD) is essential in preventing t...
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01/20/2023
A Time Series Approach to Parkinson's Disease Classification from EEG
Firstly, we present a novel representation for EEG data, a 7-variate ser...
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01/19/2023
Identification, explanation and clinical evaluation of hospital patient subtypes
We present a pipeline in which unsupervised machine learning techniques ...
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11/06/2022
Understanding the properties and limitations of contrastive learning for Out-of-Distribution detection
A recent popular approach to out-of-distribution (OOD) detection is base...
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09/08/2022
Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
Recent works have shown that tackling offline reinforcement learning (RL...
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09/08/2022
What and How of Machine Learning Transparency: Building Bespoke Explainability Tools with Interoperable Algorithmic Components
Explainability techniques for data-driven predictive models based on art...
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09/08/2022
FAT Forensics: A Python Toolbox for Implementing and Deploying Fairness, Accountability and Transparency Algorithms in Predictive Systems
Predictive systems, in particular machine learning algorithms, can take ...
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08/15/2022
Self-Supervised Multimodal Fusion Transformer for Passive Activity Recognition
The pervasiveness of Wi-Fi signals provides significant opportunities fo...
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08/08/2022
Sampling Based On Natural Image Statistics Improves Local Surrogate Explainers
Many problems in computer vision have recently been tackled using models...
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03/30/2022
The Weak Supervision Landscape
Many ways of annotating a dataset for machine learning classification ta...
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12/20/2021
Classifier Calibration: How to assess and improve predicted class probabilities: a survey
This paper provides both an introduction to and a detailed overview of t...
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11/17/2021
Uncertainty Quantification of Surrogate Explanations: an Ordinal Consensus Approach
Explainability of black-box machine learning models is crucial, in parti...
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11/16/2021
Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills
A promising approach to improve the robustness and exploration in Reinfo...
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07/09/2021
Understanding surrogate explanations: the interplay between complexity, fidelity and coverage
This paper analyses the fundamental ingredients behind surrogate explana...
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06/10/2021
On the overlooked issue of defining explanation objectives for local-surrogate explainers
Local surrogate approaches for explaining machine learning model predict...
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06/08/2021
On the relation between statistical learning and perceptual distances
It has been demonstrated many times that the behavior of the human visua...
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04/19/2021
Self-Supervised WiFi-Based Activity Recognition
Traditional approaches to activity recognition involve the use of wearab...
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03/03/2021
Self-play Learning Strategies for Resource Assignment in Open-RAN Networks
Open Radio Access Network (ORAN) is being developed with an aim to democ...
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03/03/2021
Statistical Hypothesis Testing for Class-Conditional Label Noise
In this work we aim to provide machine learning practitioners with tools...
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02/22/2021
Explainers in the Wild: Making Surrogate Explainers Robust to Distortions through Perception
Explaining the decisions of models is becoming pervasive in the image pr...
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12/02/2020
Information Theory in Density Destructors
Density destructors are differentiable and invertible transforms that ma...
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10/13/2020
Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control
In this paper we investigate the use of model-based reinforcement learni...
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10/08/2020
Information Theory Measures via Multidimensional Gaussianization
Information theory is an outstanding framework to measure uncertainty, d...
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07/03/2020
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data
There is a pressing need to automatically understand the state and progr...
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10/29/2019
bLIMEy: Surrogate Prediction Explanations Beyond LIME
Surrogate explainers of black-box machine learning predictions are of pa...
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10/28/2019
PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance
Traditionally, the vision community has devised algorithms to estimate t...
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09/20/2019
FACE: Feasible and Actionable Counterfactual Explanations
Work in Counterfactual Explanations tends to focus on the principle of "...
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09/11/2019
FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency
Machine learning algorithms can take important decisions, sometimes lega...
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08/16/2019
Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback
Recent advances in both machine learning and Internet-of-Things have att...
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08/16/2019
N2D:(Not Too) Deep clustering via clustering the local manifold of an autoencoded embedding
Deep clustering has increasingly been demonstrating superiority over con...
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08/09/2019
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance
In recent years there has been a growing interest in image generation th...
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07/01/2019
Location Anomalies Detection for Connected and Autonomous Vehicles
Future Connected and Automated Vehicles (CAV), and more generally ITS, w...
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05/31/2019
Ordinal Regression as Structured Classification
This paper extends the class of ordinal regression models with a structu...
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05/24/2019
Conditional t-SNE: Complementary t-SNE embeddings through factoring out prior information
Dimensionality reduction and manifold learning methods such as t-Distrib...
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05/23/2019
Neural ODEs with stochastic vector field mixtures
It was recently shown that neural ordinary differential equation models ...
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10/24/2018
Label Propagation for Learning with Label Proportions
Learning with Label Proportions (LLP) is the problem of recovering the u...
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06/25/2018
Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable
In this paper we study the prediction of heart rate from acceleration us...
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07/25/2011