4 papers
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…
Symmetric Linear Bandits with Hidden Symmetry
Nam Phuong Tran, The Anh Ta, Debmalya Mandal +1
High-dimensional linear bandits with low-dimensional structure have received considerable attention in recent studies due to their practical significance. The most common structure…
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…
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games
Nam Phuong Tran, The Anh Ta, Shuqing Shi +3
Reward allocation, also known as the credit assignment problem, has been an important topic in economics, engineering, and machine learning. An important concept in reward allocati…