Search Results for author: Xiaonan Liu

Found 9 papers, 0 papers with code

Adaptive Model Pruning and Personalization for Federated Learning over Wireless Networks

no code implementations4 Sep 2023 Xiaonan Liu, Tharmalingam Ratnarajah, Mathini Sellathurai, Yonina C. Eldar

This framework splits the learning model into a global part with model pruning shared with all devices to learn data representations and a personalized part to be fine-tuned for a specific device, which adapts the model size during FL to reduce both computation and communication latency and increases the learning accuracy for devices with non-independent and identically distributed data.

Federated Learning

Adaptive Federated Pruning in Hierarchical Wireless Networks

no code implementations15 May 2023 Xiaonan Liu, Shiqiang Wang, Yansha Deng, Arumugam Nallanathan

We present the convergence analysis of an upper on the l2 norm of gradients for HFL with model pruning, analyze the computation and communication latency of the proposed model pruning scheme, and formulate an optimization problem to maximize the convergence rate under a given latency threshold by jointly optimizing the pruning ratio and wireless resource allocation.

Federated Learning Privacy Preserving

Federated Learning and Meta Learning: Approaches, Applications, and Directions

no code implementations24 Oct 2022 Xiaonan Liu, Yansha Deng, Arumugam Nallanathan, Mehdi Bennis

Unlike other tutorial papers, our objective is to explore how FL, meta learning, and FedMeta methodologies can be designed, optimized, and evolved, and their applications over wireless networks.

Decision Making Federated Learning +2

Goal-Oriented Semantic Communications for 6G Networks

no code implementations17 Oct 2022 Hui Zhou, Yansha Deng, Xiaonan Liu, Nikolaos Pappas, Arumugam Nallanathan

In this article, we propose a generic goal-oriented semantic communication framework for various tasks with diverse data types, which incorporates both semantic level information and effectiveness-aware performance metrics.

Learning-based Prediction, Rendering and Transmission for Interactive Virtual Reality in RIS-Assisted Terahertz Networks

no code implementations27 Jul 2021 Xiaonan Liu, Yansha Deng, Chong Han, Marco Di Renzo

This high data rate over short transmission distances may be achieved via abundant bandwidth in the terahertz (THz) band.

Edge-computing

QoE Optimization for Live Video Streaming in UAV-to-UAV Communications via Deep Reinforcement Learning

no code implementations21 Feb 2021 Liyana Adilla binti Burhanuddin, Xiaonan Liu, Yansha Deng, Ursula Challita, Andras Zahemszky

In this paper, we co-design the video resolution, the movement, and the power control of UAV-BS and UAV-UEs to maximize the Quality of Experience (QoE) of real-time video streaming.

Learning-based Prediction and Uplink Retransmission for Wireless Virtual Reality (VR) Network

no code implementations16 Dec 2020 Xiaonan Liu, Xinyu Li, Yansha Deng

While for the online learning algorithm, based on the VR user's actual viewpoint delivered through uplink transmission, we compare it with the predicted viewpoint and update the parameters of the online learning algorithm to further improve the prediction accuracy.

Learning-based Prediction, Rendering and Association Optimization for MEC-enabled Wireless Virtual Reality (VR) Network

no code implementations17 May 2020 Xiaonan Liu, Yansha Deng

Wireless-connected Virtual Reality (VR) provides immersive experience for VR users from any-where at anytime.

STAC: Science Toolkit Based on Chinese Idiom Knowledge Graph

no code implementations WS 2019 Meiling Wang, Min Xiao, Changliang Li, Yu Guo, Zhixin Zhao, Xiaonan Liu

Chinese idioms (Cheng Yu) have seen five thousand years{'} history and culture of China, meanwhile they contain large number of scientific achievement of ancient China.

Cultural Vocal Bursts Intensity Prediction

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