6 papers
Accuracy Certificates for Convex Optimization at Accelerated Rates via Primal-Dual Averaging
Matthew X. Burns, Jiaming Liang
Many works in convex optimization provide rates for achieving a small primal gap. However, this quantity is typically unavailable in practice. In this work, we show that solving a…
Improved Analysis of Restarted Accelerated Gradient and Augmented Lagrangian Methods via Inexact Proximal Point Frameworks
Matthew X. Burns, Jiaming Liang
This paper studies a class of double-loop (inner-outer) algorithms for convex composite optimization. For unconstrained problems, we develop a restarted accelerated composite gradi…
General Oscillator-Based Ising Machine Models with Phase-Amplitude Dynamics and Polynomial Interactions
Lianlong Sun, Matthew X. Burns, Michael C. Huang
We present an oscillator model with both phase and amplitude dynamics for oscillator-based Ising machines (OIMs). The model targets combinatorial optimization problems with polynom…
Limitations in Parallel Ising Machine Networks: Theory and Practice
Matthew X. Burns, Michael C. Huang
Analog Ising machines (IMs) occupy an increasingly prominent area of computer architecture research, offering high-quality and low latency/energy solutions to intractable computing…
Provable Accuracy Bounds for Hybrid Dynamical Optimization and Sampling
Matthew X. Burns, Qingyuan Hou, Michael C. Huang
Analog dynamical accelerators (DXs) are a growing sub-field in computer architecture research, offering order-of-magnitude gains in power efficiency and latency over traditional di…
GALIC: Hybrid Multi-Qubitwise Pauli Grouping for Quantum Computing Measurement
Matthew X. Burns, Chenxu Liu, Samuel Stein +3
Observable estimation is a core primitive in NISQ-era algorithms targeting quantum chemistry applications. To reduce the state preparation overhead required for accurate estimation…