8 citations · 17 across the 11 of their papers we have counts for
4 papers · 1 filter
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…
Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification
Anshuka Rangi, Long Tran-Thanh, Haifeng Xu +1
We study bandit algorithms under data poisoning attacks in a bounded reward setting. We consider a strong attacker model in which the attacker can observe both the selected actions…
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…