100 citations · 229 across the 26 of their papers we have counts for
7 papers · 1 filter
Revisiting LARS for Large Batch Training Generalization of Neural Networks
Khoi Do, Duong Nguyen, Hoa Nguyen +3
This paper explores Large Batch Training techniques using layer-wise adaptive scaling ratio (LARS) across diverse settings, uncovering insights. LARS algorithms with warm-up tend t…
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…
Temporal Multiresolution Graph Neural Networks For Epidemic Prediction
Truong Son Hy, Viet Bach Nguyen, Long Tran-Thanh +1
In this paper, we introduce Temporal Multiresolution Graph Neural Networks (TMGNN), the first architecture that both learns to construct the multiscale and multiresolution graph st…
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…
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…
Streaming Bayesian Inference for Crowdsourced Classification
Edoardo Manino, Long Tran-Thanh, Nicholas R. Jennings
A key challenge in crowdsourcing is inferring the ground truth from noisy and unreliable data. To do so, existing approaches rely on collecting redundant information from the crowd…
Unifying the stochastic and the adversarial Bandits with Knapsack
Anshuka Rangi, Massimo Franceschetti, Long Tran-Thanh
This paper investigates the adversarial Bandits with Knapsack (BwK) online learning problem, where a player repeatedly chooses to perform an action, pays the corresponding cost, an…