7 papers
Beyond Hardware: Adaptive Algorithmic Control by State-Proxy Equalization
Jianlong Lu, Hongrui Zhang, Vishal Sharathchandra Bajpe +2
Recent advances in quantum computing have been driven primarily by improvements in hardware. Here we show that substantial gains can instead arise from how finite computational res…
Multi-Agent Reinforcement Learning for Intraday Operating Rooms Scheduling under Uncertainty
Kailiang Liu, Ying Chen, Ralf Borndörfer +1
Intraday surgical scheduling is a multi-objective decision problem under uncertainty-balancing elective throughput, urgent and emergency demand, delays, sequence-dependent setups,…
From Coverage to Prestige: A Comprehensive Assessment of Large-Scale Scientometric Data
Guoyang Rong, Ying Chen, Thorsten Koch +1
As research in the Scientometric deepens, the impact of data quality on research outcomes has garnered increasing attention. This study, based on Web of Science (WoS) and Crossref…
Benchmarking of Quantum and Classical Computing in Large-Scale Dynamic Portfolio Optimization Under Market Frictions
Ying Chen, Thorsten Koch, Hanqiu Peng +1
Quantum computing is poised to transform the financial industry, yet its advantages over traditional methods have not been evidenced. As this technology rapidly evolves, benchmarki…
40 Years of Interdisciplinary Research: Phases, Origins, and Key Turning Points (1981-2020)
Guoyang Rong, Ying Chen, Feicheng Ma +1
This study examines the historical evolution of interdisciplinary research (IDR) over a 40-year period, focusing on its dynamic trends, phases, and key turning points. We apply tim…
Article's Scientific Prestige: measuring the impact of individual articles in the Web of Science
Ying Chen, Thorsten Koch, Nazgul Zakiyeva +5
We performed a citation analysis on the Web of Science publications consisting of more than 63 million articles and 1.45 billion citations on 254 subjects from 1981 to 2020. We pro…
The Variational Bayesian Inference for Network Autoregression Models
Wei-Ting Lai, Ray-Bing Chen, Ying Chen +1
We develop a variational Bayesian (VB) approach for estimating large-scale dynamic network models in the network autoregression framework. The VB approach allows for the automatic…