Sicong Liu
Orcid: 0000-0003-4402-1260Affiliations:
- Northwestern Polytechnical University, School of Computer Science and Engineering, Xi'an, China
- Xidian University, School of Computer Science and Technology, Xi'an, China (PhD 2020)
According to our database1,
Sicong Liu
authored at least 46 papers
between 2014 and 2025.
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Bibliography
2025
CrowdHMTware: A Cross-Level Co-Adaptation Middleware for Context-Aware Mobile DL Deployment.
IEEE Trans. Mob. Comput., August, 2025
AdaScale: Dynamic Context-Aware DNN Scaling via Automated Adaptation Loop on Mobile Devices.
IEEE Internet Things J., June, 2025
IEEE Trans. Mob. Comput., April, 2025
ClassTer: Mobile Shift-Robust Personalized Federated Learning via Class-Wise Clustering.
IEEE Trans. Mob. Comput., March, 2025
DeepSwarm: towards swarm deep learning with bi-directional optimization of data acquisition and processing.
Frontiers Comput. Sci., March, 2025
AdaKnife: Flexible DNN Offloading for Inference Acceleration on Heterogeneous Mobile Devices.
IEEE Trans. Mob. Comput., February, 2025
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025
2024
CrowdLearning: A Decentralized Distributed Training Framework Based on Collectives of Trusted AIoT Devices.
IEEE Trans. Mob. Comput., December, 2024
Size Matters: Characterizing the Effect of Target Size on Wi-Fi Sensing Based on the Fresnel Zone Model.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., November, 2024
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., November, 2024
EchoPFL: Asynchronous Personalized Federated Learning on Mobile Devices with On-Demand Staleness Control.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2024
AdaMEC: Towards a Context-adaptive and Dynamically Combinable DNN Deployment Framework for Mobile Edge Computing.
ACM Trans. Sens. Networks, January, 2024
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control.
CoRR, 2024
AdaBridge: Dynamic Data and Computation Reuse for Efficient Multi-task DNN Co-evolution in Edge Systems.
CoRR, 2024
IEEE Commun. Surv. Tutorials, 2024
AdaFlow: Opportunistic Inference on Asynchronous Mobile Data with Generalized Affinity Control.
Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024
AdaShadow: Responsive Test-time Model Adaptation in Non-stationary Mobile Environments.
Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024
Proceedings of the 2024 Workshop on Adaptive AIoT Systems, 2024
Proceedings of the 2024 Workshop on Adaptive AIoT Systems, 2024
2023
Genie in the Model: Automatic Generation of Human-in-the-Loop Deep Neural Networks for Mobile Applications.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., March, 2023
A Novel Framework for Adaptive Quadruped Robot Locomotion Learning in Uncertain Environments.
Proceedings of the Green, Pervasive, and Cloud Computing - 18th International Conference, 2023
MoEnlight: Energy-efficient and self-adaptive Low-light Video Stream Enhancement on Mobile Devices.
Proceedings of the ACM Turing Award Celebration Conference - China 2023, 2023
2022
Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic.
Inf. Process. Manag., 2022
CAQ: Toward Context-Aware and Self-Adaptive Deep Model Computation for AIoT Applications.
IEEE Internet Things J., 2022
IEEE Internet Things J., 2022
IEEE Internet Things J., 2022
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022
Frontiers Comput. Sci., 2022
Weather-oriented Domain Generalization of Semantic Segmentation for Autonomous Driving.
Proceedings of the IEEE Smartworld, 2022
Context-Adaptive Online Reinforcement Learning for Multi-view Video Summarization on Mobile Devices.
Proceedings of the 28th IEEE International Conference on Parallel and Distributed Systems, 2022
Proceedings of the IEEE International Conference on Communications, 2022
2021
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles.
IEEE Trans. Mob. Comput., 2021
Context-aware Adaptive Surgery: A Fast and Effective Framework for Adaptative Model Partition.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021
AdaSpring: Context-adaptive and Runtime-evolutionary Deep Model Compression for Mobile Applications.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2021
Towards information-rich, logical dialogue systems with knowledge-enhanced neural models.
Neurocomputing, 2021
Decentralized Multi-AGV Task Allocation based on Multi-Agent Reinforcement Learning with Information Potential Field Rewards.
Proceedings of the IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems, 2021
JointCS: Joint Search for Deep Model Compression and Segmentation on Heterogeneous IoT Devices.
Proceedings of the 27th IEEE International Conference on Parallel and Distributed Systems, 2021
TL-SDD: A Transfer Learning-Based Method for Surface Defect Detection with Few Samples.
Proceedings of the 7th International Conference on Big Data Computing and Communications, 2021
2020
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles.
CoRR, 2020
CrowdDepict: Know What and How to Generate Personalized and Logical Product Description using Crowd intelligence.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020
2018
On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework.
Proceedings of the 16th Annual International Conference on Mobile Systems, 2018
2017
UbiEar: Bringing Location-independent Sound Awareness to the Hard-of-hearing People with Smartphones.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017
Understanding Sensor Data Using Deep Learning Methods on Resource-Constrained Edge Devices.
Proceedings of the Wireless Sensor Networks, 2017
2016
Proceedings of the Wireless Algorithms, Systems, and Applications, 2016
Proceedings of the International Conference on Computer, 2016
2014
Lightweight construction of the information potential field in wireless sensor networks.
Proceedings of the 23rd International Conference on Computer Communication and Networks, 2014