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02/27/2022
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption
This work presents a novel protocol for fast secure inference of neural ...
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12/21/2021
Distributed Machine Learning and the Semblance of Trust
The utilisation of large and diverse datasets for machine learning (ML) ...
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12/02/2021
FedRAD: Federated Robust Adaptive Distillation
The robustness of federated learning (FL) is vital for the distributed t...
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09/06/2021
Statistical Privacy Guarantees of Machine Learning Preprocessing Techniques
Differential privacy provides strong privacy guarantees for machine lear...
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12/10/2020
Privacy-preserving medical image analysis
The utilisation of artificial intelligence in medicine and healthcare ha...
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11/15/2020
2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments
Federated Learning harnesses data from multiple sources to build a singl...
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11/10/2020
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification
This work provides a comprehensive review of existing frameworks based o...
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09/17/2020
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
Federated learning (FL) has enabled training models collaboratively from...
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10/12/2019
A blockchain-orchestrated Federated Learning architecture for healthcare consortia
We propose a novel architecture for federated learning within healthcare...
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11/09/2018
A generic framework for privacy preserving deep learning
We detail a new framework for privacy preserving deep learning and discu...
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06/08/2018
Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents
We propose a fully automatic method to find standardized view planes in ...
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03/25/2018
Learning-Based Quality Control for Cardiac MR Images
The effectiveness of a cardiovascular magnetic resonance (CMR) scan depe...
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11/15/2016
Comparison of Brain Networks with Unknown Correspondences
Graph theory has drawn a lot of attention in the field of Neuroscience d...
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11/10/2016
Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016
Understanding brain connectivity in a network-theoretic context has show...
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06/03/2016
Learning under Distributed Weak Supervision
The availability of training data for supervision is a frequently encoun...
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05/25/2016
