10 papers
Online Scheduling for Throughput Maximization of Time-varying Markovian Channels with Unknown Statistics
Tasmeen Zaman Ornee, Clement Kam, Ness B. Shroff
We consider a wireless scheduling problem in downlink wireless networks with unknown channel statistics, where a Base Station (BS) sends data to multiple users. The scheduling perf…
Abstractions for Network Intelligence: A Reference Architecture for AI at the Wireless Edge
Salil Reddy, Haohuang Wen, Ness Shroff +5
Networks are increasingly adopting AI as are AI applications leveraging networks. Awareness sharing between networks and AI applications promises to unlock higher levels of network…
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…
FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models
Fatemeh Nourzad, Amirhossein Roknilamouki, Eylem Ekici +2
Aligning Large Language Models (LLMs) with human values often involves balancing multiple, conflicting objectives such as helpfulness and harmlessness. Training these models is com…
Beyond Freshness and Semantics: A Coupon-Collector Framework for Effective Status Updates
Youssef Ahmed, Arnob Ghosh, Chih-Chun Wang +1
For status update systems operating over unreliable energy-constrained wireless channels, we address Weaver's long-standing Level-C question: do my packets actually improve the pla…
Near-Optimal Partially Observable Reinforcement Learning with Partial Online State Information
Ming Shi, Yingbin Liang, Ness B. Shroff
Partially observable Markov decision processes (POMDPs) are a general framework for sequential decision-making under latent state uncertainty, yet learning in POMDPs is intractable…