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Advanced Topics in AI for Networking (Summer 2023): Difference between revisions
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Advanced Topics in AI for Networking (Summer 2023) (view source)
Revision as of 09:58, 13 April 2023
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==List of Papers == | ==List of Papers == | ||
1 | 1. Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition [https://dl.acm.org/doi/pdf/10.1145/3495243.3560519] | ||
14. | 2. Learning for Crowdsourcing: Online Dispatch for Video Analytics with Guarantee [https://ieeexplore.ieee.org/document/9796960] | ||
3. CASVA: Configuration-Adaptive Streaming for Live Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796875] | |||
4. Batch Adaptative Streaming for Video Analytics [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796853] | |||
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] | |||
6. AoI-minimal UAV Crowdsensing by Model-based Graph Convolutional Reinforcement Learning [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796732] | |||
7. RouteNet-Erlang: A Graph Neural Network for Network Performance Evaluation [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796944] | |||
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] | |||
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] | |||
10. FeCo: Boosting Intrusion Detection Capability in IoT Networks via Contrastive Learning [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796926] | |||
11. TrojanFlow: A Neural Backdoor Attack to Deep Learning-based Network Traffic Classifiers [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796878] | |||
12. Mousika: Enable General In-Network Intelligence in Programmable Switches by Knowledge Distillation [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9796936] | |||
13. Ekya: Continuous Learning of Video Analytics Models on Edge Compute Servers [https://www.usenix.org/conference/nsdi22/presentation/bhardwaj] | |||
14. Top-K Deep Video Analytics: A Probabilistic Approach [https://dl.acm.org/doi/pdf/10.1145/3448016.3452786] | |||
15. Delay-Aware Microservice Coordination in Mobile Edge Computing: A Reinforcement Learning Approach [https://ieeexplore.ieee.org/document/8924682] | |||
16. Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments Using A3C Learning and Residual Recurrent Neural Networks [https://ieeexplore.ieee.org/document/9169832] | |||
17. Multi-Task Federated Learning for Personalised Deep Neural Networks in Edge Computing [https://ieeexplore.ieee.org/document/9492755] | |||
18. Leveraging Deep Reinforcement Learning With Attention Mechanism for Virtual Network Function Placement and Routing [https://ieeexplore.ieee.org/document/10029903] | |||
19. Pyramid: Enabling Hierarchical Neural Networks with Edge Computing [https://dl.acm.org/doi/10.1145/3485447.3511990] | |||
20. Index-aware reinforcement learning for adaptive video streaming at the wireless edge [https://dl.acm.org/doi/10.1145/3492866.3549726] | |||
==Schedule== | ==Schedule== | ||
W1: Open Talk (13.4) | W1: Open Talk (13.4) | ||
W2: | W2: Select papers and create schedule | ||
W4: Paper ID: | W4: Paper ID: | ||
W6: ... | |||
W8: ... | |||
W10: ... | |||
W12: ... | |||
W14: .. | |||
'''!! xx.xx deadline for registration on Flexnow''' | '''!! xx.xx deadline for registration on Flexnow''' | ||