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ORCIDNetAI@SIGCOMM 2019: Beijing, China
- Proceedings of the 2019 Workshop on Network Meets AI & ML, NetAI@SIGCOMM 2019, Beijing, China, August 23, 2019. ACM 2019, ISBN 978-1-4503-6872-8
- Apoorv Shukla, Kevin Nico Hudemann, Artur Hecker
, Stefan Schmid:
Runtime Verification of P4 Switches with Reinforcement Learning. 1-7 - Johannes Zerwas, Patrick Kalmbach, Laurenz Henkel, Gábor Rétvári, Wolfgang Kellerer, Andreas Blenk, Stefan Schmid:
NetBOA: Self-Driving Network Benchmarking. 8-14 - Hyojoon Kim, Arpit Gupta:
ONTAS: Flexible and Scalable Online Network Traffic Anonymization System. 15-21 - Lin Zhu, Juan Zhao, Yiting Wang, Juanlan Feng, Chao Deng, Hui Li:
Smart Prediction of the Complaint Hotspot Problem in Mobile Network. 22-28 - Arnaud Dethise, Marco Canini, Srikanth Kandula:
Cracking Open the Black Box: What Observations Can Tell Us About Reinforcement Learning Agents. 29-36 - Constantin Sander, Jan Rüth, Oliver Hohlfeld, Klaus Wehrle:
DeePCCI: Deep Learning-based Passive Congestion Control Identification. 37-43 - Vidit Saxena, Joakim Jaldén, Joseph E. Gonzalez, Mats Bengtsson, Hugo M. Tullberg, Ion Stoica:
Contextual Multi-Armed Bandits for Link Adaptation in Cellular Networks. 44-49 - Meng Qin, Kai Lei, Bo Bai, Gong Zhang:
Towards a Profiling View for Unsupervised Traffic Classification by Exploring the Statistic Features and Link Patterns. 50-56 - Vadim Kirilin, Aditya Sundarrajan, Sergey Gorinsky, Ramesh K. Sitaraman:
RL-Cache: Learning-Based Cache Admission for Content Delivery. 57-63 - Sharat Chandra Madanapalli, Hassan Habibi Gharakheili, Vijay Sivaraman:
Assisting Delay and Bandwidth Sensitive Applications in a Self-Driving Network. 64-69 - Anu Mercian, Puneet Sharma, Renato Aguiar, Chinlin Chen, David Pinheiro:
UDAAN: Embedding User-Defined Analytics Applications in Network Devices. 70-75 - Deniz Üstebay, Jie Chuai:
Hierarchical Bayesian Modelling for Wireless Cellular Networks. 76-82 - Yafim Kazak, Clark W. Barrett, Guy Katz, Michael Schapira:
Verifying Deep-RL-Driven Systems. 83-89
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