Abstract: Sparse signal recovery arises from many applications. However, deterministic algorithms often require significant time, especially for large-scale systems. Hence, stochastic algorithms like ...

Abstract: This article proposes a framework to study the convergence of stochastic optimization and learning algorithms. The framework is modeled over the different challenges that these algorithms ...

Multistate Markov models are frequently used to characterize disease processes, but their estimation from longitudinal data is often hampered by complex patterns of incompleteness. Two algorithms for ...

The difficulties of algorithmic dynamics in highly nonconvex landscapes are central in several research areas, from hard combinatorial optimization to machine learning. However, it is unclear why and ...

Classical randomness has emerged as an important tool in addressing the challenge of designing quantum protocols and algorithms. Current methods for calibrating and evaluating quantum gates, like ...

Extension of the project PRISM-games [https://github.com/prismmodelchecker/prism-games] with the algorithms as described in GandALF'20 paper "Comparison of Algorithms ...

Ali Baba and the Forty Thieves is a novel meta-heuristic algorithm for solving numerical optimization problems. The algorithm is inspired by the story of Ali Baba and the Forty Thieves. The algorithm ...