no code implementations • 23 Nov 2023 • Sikha Pentyala, Shubham Sharma, Sanjay Kariyappa, Freddy Lecue, Daniele Magazzeni
We observe that PrivRecourse can provide paths that are private and realistic.
no code implementations • 6 Mar 2023 • Jia Ao Sun, Sikha Pentyala, Martine De Cock, Golnoosh Farnadi
Users worldwide access massive amounts of curated data in the form of rankings on a daily basis.
no code implementations • 13 Oct 2022 • Mayana Pereira, Sikha Pentyala, Anderson Nascimento, Rafael T. de Sousa Jr., Martine De Cock
Legal and ethical restrictions on accessing relevant data inhibit data science research in critical domains such as health, finance, and education.
no code implementations • 23 May 2022 • Sikha Pentyala, Nicola Neophytou, Anderson Nascimento, Martine De Cock, Golnoosh Farnadi
Group fairness ensures that the outcome of machine learning (ML) based decision making systems are not biased towards a certain group of people defined by a sensitive attribute such as gender or ethnicity.
1 code implementation • 8 Feb 2022 • Sikha Pentyala, David Melanson, Martine De Cock, Golnoosh Farnadi
Machine learning (ML) has become prominent in applications that directly affect people's quality of life, including in healthcare, justice, and finance.
no code implementations • 5 Feb 2022 • Sikha Pentyala, Davis Railsback, Ricardo Maia, Rafael Dowsley, David Melanson, Anderson Nascimento, Martine De Cock
We address the problem of learning a machine learning model from training data that originates at multiple data owners while providing formal privacy guarantees regarding the protection of each owner's data.
no code implementations • 6 Feb 2021 • Sikha Pentyala, Rafael Dowsley, Martine De Cock
We propose a privacy-preserving implementation of single-frame method based video classification with convolutional neural networks that allows a party to infer a label from a video without necessitating the video owner to disclose their video to other entities in an unencrypted manner.