Search Results for author: Wiebke Toussaint

Found 7 papers, 3 papers with code

Tiny, always-on and fragile: Bias propagation through design choices in on-device machine learning workflows

1 code implementation19 Jan 2022 Wiebke Toussaint, Aaron Yi Ding, Fahim Kawsar, Akhil Mathur

Billions of distributed, heterogeneous and resource constrained IoT devices deploy on-device machine learning (ML) for private, fast and offline inference on personal data.

Keyword Spotting

SVEva Fair: A Framework for Evaluating Fairness in Speaker Verification

2 code implementations26 Jul 2021 Wiebke Toussaint, Aaron Yi Ding

Despite the success of deep neural networks (DNNs) in enabling on-device voice assistants, increasing evidence of bias and discrimination in machine learning is raising the urgency of investigating the fairness of these systems.

Fairness Speaker Verification +2

Machine Learning Systems in the IoT: Trustworthiness Trade-offs for Edge Intelligence

no code implementations1 Dec 2020 Wiebke Toussaint, Aaron Yi Ding

Machine learning systems (MLSys) are emerging in the Internet of Things (IoT) to provision edge intelligence, which is paving our way towards the vision of ubiquitous intelligence.

BIG-bench Machine Learning

Clustering Residential Electricity Consumption Data to Create Archetypes that Capture Household Behaviour in South Africa

1 code implementation11 Jun 2020 Wiebke Toussaint, Deshendran Moodley

While internal clustering validation measures are well established in the electricity domain, they are limited for selecting useful clusters.

Clustering Time Series Clustering

Using competency questions to select optimal clustering structures for residential energy consumption patterns

no code implementations1 Jun 2020 Wiebke Toussaint, Deshendran Moodley

During cluster analysis domain experts and visual analysis are frequently relied on to identify the optimal clustering structure.


Machine Learning Systems for Intelligent Services in the IoT: A Survey

no code implementations29 May 2020 Wiebke Toussaint, Aaron Yi Ding

Machine learning (ML) technologies are emerging in the Internet of Things (IoT) to provision intelligent services.

BIG-bench Machine Learning

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