3 papers
cs.LG2026
Pruning at Initialisation through the lens of Graphon Limit: Convergence, Expressivity, and Generalisation
Hoang Pham, The-Anh Ta, Long Tran-Thanh
Pruning at Initialisation methods discover sparse, trainable subnetworks before training, but their theoretical mechanisms remain elusive. Existing analyses are often limited to fi…
cs.LG2025
The Graphon Limit Hypothesis: Understanding Neural Network Pruning via Infinite Width Analysis
Hoang Pham, The-Anh Ta, Tom Jacobs +2
Sparse neural networks promise efficiency, yet training them effectively remains a fundamental challenge. Despite advances in pruning methods that create sparse architectures, unde…
cs.LG2024
Flatness-aware Sequential Learning Generates Resilient Backdoors
Hoang Pham, The-Anh Ta, Anh Tran +1
Recently, backdoor attacks have become an emerging threat to the security of machine learning models. From the adversary's perspective, the implanted backdoors should be resistant…