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 | 12:00 | 12:15 | Welcome by Andreas Blenk and Prof. Kellerer | | 12:00 | 12:15 | Welcome by Andreas Blenk and Prof. Kellerer |
 | 12:15 | 13:15 | **Session 1: Can ML finally solve congestion control problems?** \\  Session chair: Andreas Blenk (TUM) \\ \\ __Talk 1__: //Using Deep Learning in Network Measurements for Passive Congestion Control Identification//;​ C. Sander, J. Rüth (RWTH Aachen), O. Hohlfeld, K. Wehrle (BTU) \\  \\ __Talk 2__: //TCP Congestion Control Using Imitation Learning//; B. Jaeger, J. Schmeißer (TUM) | | 12:15 | 13:15 | **Session 1: Can ML finally solve congestion control problems?** \\  Session chair: Andreas Blenk (TUM) \\ \\ __Talk 1__: //Using Deep Learning in Network Measurements for Passive Congestion Control Identification//;​ C. Sander, J. Rüth (RWTH Aachen), O. Hohlfeld, K. Wehrle (BTU) \\  \\ __Talk 2__: //TCP Congestion Control Using Imitation Learning//; B. Jaeger, J. Schmeißer (TUM) |
-| 13:15 | 13:45 | **Teaser Session for Posters and Demos** \\ \\ * NOracle: Who is communicating with whom in my network? (TUM-LKN) ​ \\ * The Softwarised Data Zoo (UPB) \\ * Learning from Hierarchical Heavy Hitters (KIT) \\ * Artificial Intelligence and Machine Learning at LKN (TUM-LKN) \\ * FlexNets: Quantifiying Flexibility in Communication Networks (TUM-LKN) \\ * Veni Vidi Dixi: reliable wireless communication with depth images (TUM-LKN) \\ *  NCSbench: Reproducible Benchmarking Platform for NCS (TUM-LKN) +| 13:15 | 13:45 | **Teaser Session for Posters and Demos** \\ \\ * NOracle: Who is communicating with whom in my network? (TUM-LKN) ​ \\ * The Softwarised Data Zoo (UPB) \\ * Learning from Hierarchical Heavy Hitters (KIT) \\ * Artificial Intelligence and Machine Learning at LKN (TUM-LKN) \\ * FlexNets: Quantifiying Flexibility in Communication Networks (TUM-LKN) \\ * Veni Vidi Dixi: reliable wireless communication with depth images (TUM-LKN) \\ *  NCSbench: Reproducible Benchmarking Platform for NCS (TUM-LKN) |
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 | 13:45 | 14:15 | Short Break with Posters and Demos | | 13:45 | 14:15 | Short Break with Posters and Demos |
 | 14:15 | 15:45 | **Session 2: ML for Network Modeling** \\ Session chair: Stefan Schneider (UPB)  \\ \\ __Talk 1__: //DeepMPLS: Fast Analysis of MPLS Configurations Using Deep Learning//; F. Geyer (TUM) \\ \\ __Talk 2__: //Runtime Verification of P4 Switches with Reinforcement Learning//; A. Shukla, K. N. Hudemann (TU Berlin), A. Hecker (Huawei), S. Schmid (University of Vienna) \\ \\ __Talk 3__: //​Optimising the Performance of Deep Transfer Learning for Communication Networking Applications//;​ T. V. Phan, T. Bauschert (TU Chemnitz) | | 14:15 | 15:45 | **Session 2: ML for Network Modeling** \\ Session chair: Stefan Schneider (UPB)  \\ \\ __Talk 1__: //DeepMPLS: Fast Analysis of MPLS Configurations Using Deep Learning//; F. Geyer (TUM) \\ \\ __Talk 2__: //Runtime Verification of P4 Switches with Reinforcement Learning//; A. Shukla, K. N. Hudemann (TU Berlin), A. Hecker (Huawei), S. Schmid (University of Vienna) \\ \\ __Talk 3__: //​Optimising the Performance of Deep Transfer Learning for Communication Networking Applications//;​ T. V. Phan, T. Bauschert (TU Chemnitz) |
home.txt · Last modified: 2020/02/20 11:45 by guest