6 citations · 6 across the 10 of their papers we have counts for
10 papers
When Mobile Crowdsourcing Meets Queueing Systems: Human-in-the-Loop Learning
Hongbo Li, Lingjie Duan, Ness B. Shroff
In service systems, customers now rely on congestion information before deciding which queue or server to join, from restaurants and theme-park attractions to road networks. We stu…
To Theoretically Understand Transformer-Based In-Context Learning for Optimizing CSMA
Shugang Hao, Hongbo Li, Lingjie Duan
The binary exponential backoff scheme is widely used in WiFi 7 and still incurs poor throughput performance under dynamic channel environments. Recent model-based approaches (e.g.,…
Provable In-Context Learning of Nonlinear Regression with Transformers
Hongbo Li, Lingjie Duan, Yingbin Liang
The transformer architecture, which processes sequences of input tokens to produce outputs for query tokens, has revolutionized numerous areas of machine learning. A defining featu…
Competitive Multi-armed Bandit Games for Resource Sharing
Hongbo Li, Lingjie Duan
In modern resource-sharing systems, multiple agents access limited resources with unknown stochastic conditions to perform tasks. When multiple agents access the same resource (arm…
To Analyze and Regulate Human-in-the-loop Learning for Congestion Games
Hongbo Li, Lingjie Duan
In congestion games, selfish users behave myopically to crowd to the shortest paths, and the social planner designs mechanisms to regulate such selfish routing through information…
Theory of Mixture-of-Experts for Mobile Edge Computing
Hongbo Li, Lingjie Duan
In mobile edge computing (MEC) networks, mobile users generate diverse machine learning tasks dynamically over time. These tasks are typically offloaded to the nearest available ed…
To Optimize Human-in-the-loop Learning in Repeated Routing Games
Hongbo Li, Lingjie Duan
Today navigation applications (e.g., Waze and Google Maps) enable human users to learn and share the latest traffic observations, yet such information sharing simply aids selfish u…
Theory on Mixture-of-Experts in Continual Learning
Hongbo Li, Sen Lin, Lingjie Duan +2
Continual learning (CL) has garnered significant attention because of its ability to adapt to new tasks that arrive over time. Catastrophic forgetting (of old tasks) has been ident…
Distributed Learning for Dynamic Congestion Games
Hongbo Li, Lingjie Duan
Today mobile users learn and share their traffic observations via crowdsourcing platforms (e.g., Google Maps and Waze). Yet such platforms myopically recommend the currently shorte…
Human-in-the-loop Learning for Dynamic Congestion Games
Hongbo Li, Lingjie Duan
Today mobile users learn and share their traffic observations via crowdsourcing platforms (e.g., Waze). Yet such platforms simply cater to selfish users' myopic interests to recomm…