Advanced Topics in AI for Networking (Winter 2023/2024): Difference between revisions

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==List of Papers ==
==List of Papers ==
1. Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition [https://dl.acm.org/doi/pdf/10.1145/3495243.3560519]
1. FedAdapter: Efficient Federated Learning for Modern NLP [https://arxiv.org/pdf/2205.10162.pdf]


2. Learning for Crowdsourcing: Online Dispatch for Video Analytics with Guarantee [https://ieeexplore.ieee.org/document/9796960]  
2. AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving [https://dl.acm.org/doi/10.1145/3570361.3592517]


3. CASVA: Configuration-Adaptive Streaming for Live Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796875]
3. mmFER: Millimetre-wave Radar based Facial Expression Recognition for Multimedia IoT Applications [https://dl.acm.org/doi/10.1145/3570361.3592515]


4. Batch Adaptative Streaming for Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796853]
4. NeRF2: Neural Radio-Frequency Radiance Fields [https://dl.acm.org/doi/10.1145/3570361.3592527]


5. FlexPatch: Fast and Accurate Object Detection for On-device High-Resolution Live Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796984]
5. Exploiting Contactless Side Channels in Wireless Charging Power Banks for User Privacy Inference via Few-shot Learning [https://dl.acm.org/doi/10.1145/3570361.3613288]


6. AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796732]
6. Practically Adopting Human Activity Recognition [https://dl.acm.org/doi/10.1145/3570361.3613299]


7. RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796944]
7. Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition [https://dl.acm.org/doi/pdf/10.1145/3495243.3560519]


8. Deep Reinforcement Learning-Based Control Framework for Radio Access Networks [https://dl.acm.org/doi/pdf/10.1145/3495243.3558276?casa_token=IlUioU8GgjwAAAAA:ygqCMlQv28WBdO-z65UXYjJIoeVoyEiwVI00D5nw_cNW0N6aHZCEdBzqt5r2A8jGT7pYuU8xJMJGIrs]
8. Learning for Crowdsourcing: Online Dispatch for Video Analytics with Guarantee [https://ieeexplore.ieee.org/document/9796960]  


9. NeuLens: Spatial-based Dynamic Acceleration of Convolutional Neural Networks on Edge [https://dl.acm.org/doi/pdf/10.1145/3495243.3560528?casa_token=mrLc2kitFkcAAAAA:lKf6MnXcwXxhr0SrODcIX7qP7DrthKc_yp7jZ-2MYoxmnutM4lHPuYXD5DrLrBjS38S15TbVwPSD-NA]
9. CASVA: Configuration-Adaptive Streaming for Live Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796875]


10. FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796926]
10. Batch Adaptative Streaming for Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796853]


11. TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796878]
11. FlexPatch: Fast and Accurate Object Detection for On-device High-Resolution Live Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796984]


12. Mousika: Enable General In-Network Intelligence in Programmable Switches by Knowledge Distillation [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796936]
12. AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796732]


13. Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers [https://www.usenix.org/conference/nsdi22/presentation/bhardwaj]
13. RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796944]


14. Top-K Deep Video Analytics: A Probabilistic Approach [https://dl.acm.org/doi/pdf/10.1145/3448016.3452786]
14. Deep Reinforcement Learning-Based Control Framework for Radio Access Networks [https://dl.acm.org/doi/pdf/10.1145/3495243.3558276?casa_token=IlUioU8GgjwAAAAA:ygqCMlQv28WBdO-z65UXYjJIoeVoyEiwVI00D5nw_cNW0N6aHZCEdBzqt5r2A8jGT7pYuU8xJMJGIrs]


15. Delay-Aware Microservice Coordination in Mobile Edge Computing: A Reinforcement Learning Approach [https://ieeexplore.ieee.org/document/8924682]
15. NeuLens: Spatial-based Dynamic Acceleration of Convolutional Neural Networks on Edge [https://dl.acm.org/doi/pdf/10.1145/3495243.3560528?casa_token=mrLc2kitFkcAAAAA:lKf6MnXcwXxhr0SrODcIX7qP7DrthKc_yp7jZ-2MYoxmnutM4lHPuYXD5DrLrBjS38S15TbVwPSD-NA]


16. Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments Using A3C Learning and Residual Recurrent Neural Networks [https://ieeexplore.ieee.org/document/9169832]
16. FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796926]


17. Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing [https://ieeexplore.ieee.org/document/9492755]
17. TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796878]


18. Leveraging Deep Reinforcement Learning With Attention Mechanism for Virtual Network Function Placement and Routing [https://ieeexplore.ieee.org/document/10029903]
18. Mousika: Enable General In-Network Intelligence in Programmable Switches by Knowledge Distillation [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796936]


19. Pyramid: Enabling Hierarchical Neural Networks with Edge Computing [https://dl.acm.org/doi/10.1145/3485447.3511990]
19. Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers [https://www.usenix.org/conference/nsdi22/presentation/bhardwaj]


20. Index-aware reinforcement learning for adaptive video streaming at the wireless edge [https://dl.acm.org/doi/10.1145/3492866.3549726]
20. Top-K Deep Video Analytics: A Probabilistic Approach [https://dl.acm.org/doi/pdf/10.1145/3448016.3452786]


==Schedule==
==Schedule==
Wwu1
61

edits

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