Paper-Conference

Learning to Help in Multi-Class Settings
Deploying complex machine learning models on resource-constrained devices is challenging due to limited computational power, memory, …
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Timely and Energy-Efficient Multi-Step Update Processing
This work explores systems where source updates require multiple sequential processing steps. We model and analyze the Age of …
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Timely Offloading in Mobile Edge Cloud Systems
Future real-time applications like smart cities will use complex Machine Learning (ML) models for a variety of tasks. Timely status …
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Efficient and Timely Memory Access
This paper investigates the optimization of memory sampling in status updating systems, where source updates are published in shared …
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Mitigating Data Injection Attacks on Federated Learning
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C-DIEGO: An Algorithm with Near-Optimal Sample Complexity for Distributed, Streaming PCA
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Invited Paper: Intelligent Agent Support for Achieving Low Latency in Cloud-Native NextG Mobile Core Networks
Next-generation mobile core networks are being designed to support a variety of latency sensitive applications based on emerging …
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Lock-based or Lock-less: Which Is Fresh?
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Timely Mobile Routing: An Experimental Study
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Timely Processing Of Updates From Multiple Sources
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