8 citations · 10 across the 7 of their papers we have counts for
20 papers
Label driven Knowledge Distillation for Federated Learning with non-IID Data
Minh-Duong Nguyen, Quoc-Viet Pham, Dinh Thai Hoang +3
In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an envi…
Optimising Resource Management for Embedded Machine Learning
Lei Xun, Long Tran-Thanh, Bashir M Al-Hashimi +1
Machine learning inference is increasingly being executed locally on mobile and embedded platforms, due to the clear advantages in latency, privacy and connectivity. In this paper,…
Incremental Training and Group Convolution Pruning for Runtime DNN Performance Scaling on Heterogeneous Embedded Platforms
Lei Xun, Long Tran-Thanh, Bashir M Al-Hashimi +1
Inference for Deep Neural Networks is increasingly being executed locally on mobile and embedded platforms due to its advantages in latency, privacy and connectivity. Since modern…
Sequential Choice Bandits with Feedback for Personalizing users' experience
Anshuka Rangi, Massimo Franceschetti, Long Tran-Thanh
In this work, we study sequential choice bandits with feedback. We propose bandit algorithms for a platform that personalizes users' experience to maximize its rewards. For each ac…
Zealotry and Influence Maximization in the Voter Model: When to Target Zealots?
Guillermo Romero Moreno, Edoardo Manino, Long Tran-Thanh +1
In this paper, we study influence maximization in the voter model in the presence of biased voters (or zealots) on complex networks. Under what conditions should an external contro…
Fuzzy c-Means Clustering for Persistence Diagrams
Thomas Davies, Jack Aspinall, Bryan Wilder +1
Persistence diagrams concisely represent the topology of a point cloud whilst having strong theoretical guarantees, but the question of how to best integrate this information into…