1 citations · 2 across the 15 of their papers we have counts for
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Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity
Sarah Kiden, Bernd Stahl, Beverley Townsend +22
This report presents a comprehensive response to the United Nation's Interim Report on Governing Artificial Intelligence (AI) for Humanity. It emphasizes the transformative potenti…
Federated and differentially private estimation of KL divergence
Mary Scott, Sayan Biswas, Graham Cormode +1
Measuring distribution drifts is a key task in managing distributed, sensitive data, as it underpins a wide range of federated learning and analytics applications. In many practica…
Towards Robust Federated Analytics via Differentially Private Measurements of Statistical Heterogeneity
Mary Scott, Graham Cormode, Carsten Maple
Statistical heterogeneity is a measure of how skewed the samples of a dataset are. It is a common problem in the study of differential privacy that the usage of a statistically het…
Privacy-preserving Fuzzy Name Matching for Sharing Financial Intelligence
Harsh Kasyap, Ugur Ilker Atmaca, Carsten Maple +2
Financial institutions rely on data for many operations, including a need to drive efficiency, enhance services and prevent financial crime. Data sharing across an organisation or…
Representation Noising: A Defence Mechanism Against Harmful Finetuning
Domenic Rosati, Jan Wehner, Kai Williams +7
Releasing open-source large language models (LLMs) presents a dual-use risk since bad actors can easily fine-tune these models for harmful purposes. Even without the open release o…
AI security and cyber risk in IoT systems
Petar Radanliev, David De Roure, Carsten Maple +3
We present a dependency model tailored to the context of current challenges in data strategies and make recommendations for the cybersecurity community. The model can be used for c…