375 citations · 1k across the 24 of their papers we have counts for
25 papers
Improved Convergence Bounds For Operator Splitting Algorithms With Rare Extreme Errors
Anis Hamadouche, Andrew M. Wallace, Joao F. C. Mota
In this paper, we improve upon our previous work[24,22] and establish convergence bounds on the objective function values of approximate proximal-gradient descent (AxPGD), approxim…
A Low-Power Hardware-Friendly Optimisation Algorithm With Absolute Numerical Stability and Convergence Guarantees
Anis Hamadouche, Yun Wu, Andrew M. Wallace +1
We propose Dual-Feedback Generalized Proximal Gradient Descent (DFGPGD) as a new, hardware-friendly, operator splitting algorithm. We then establish convergence guarantees under ap…
The Topology-Overlap Trade-Off in Retinal Arteriole-Venule Segmentation
Angel Victor Juanco Muller, Joao F. C. Mota, Keith A. Goatman +1
Retinal fundus images can be an invaluable diagnosis tool for screening epidemic diseases like hypertension or diabetes. And they become especially useful when the arterioles and v…
Measurement-Consistent Networks via a Deep Implicit Layer for Solving Inverse Problems
Rahul Mourya, João F. C. Mota
End-to-end deep neural networks (DNNs) have become the state-of-the-art (SOTA) for solving inverse problems. Despite their outstanding performance, during deployment, such networks…
Probabilistic Verification of Approximate Algorithms with Unstructured Errors: Application to Fully Inexact Generalized ADMM
Anis Hamadouche, Yun Wu, Andrew M. Wallace +1
We analyse the convergence of an approximate, fully inexact, ADMM algorithm under additive, deterministic and probabilistic error models. We consider the generalized ADMM scheme th…
Sharper Bounds for Proximal Gradient Algorithms with Errors
Anis Hamadouche, Yun Wu, Andrew M. Wallace +1
We analyse the convergence of the proximal gradient algorithm for convex composite problems in the presence of gradient and proximal computational inaccuracies. We derive new tight…