Quantum simulation via stochastic combination of unitaries
• Abstract Quantum simulation algorithms often require numerous ancilla qubits and deep circuits, prohibitive for near-term hardware. • We introduce a framework for simulating quan
Stochastic
Preconditioned inexact stochastic ADMM for deep models
• Abstract Deep learning models are usually trained with stochastic gradient descent-based algorithms, but these optimizers face inherent limitations, such as slow convergence and
Quantum simulation via stochastic combination of unitaries
• Abstract Quantum simulation algorithms often require numerous ancilla qubits and deep circuits, prohibitive for near-term hardware. • We introduce a framework for simulating quan
Preconditioned inexact stochastic ADMM for deep models
• Abstract Deep learning models are usually trained with stochastic gradient descent-based algorithms, but these optimizers face inherent limitations, such as slow convergence and
RIS Control through the Lens of Stochastic Network Calculus: An O-RAN Framework for Delay-Sensitive 6G Applications
• Computer Science > Networking and Internet Architecture [Submitted on 19 Feb 2026] Title:RIS Control through the Lens of Stochastic Network Calculus: An O-RAN Framework for Delay