… we present our reinforcement learningbased method for available bandwidth estimation where
we … experiments and available bandwidth estimation results employing the direct probing …

… , Experimental comparison of machine learning-based available bandwidth estimation methods
… Chou and Bo-Chun Wang, A machine learning-based approach for estimating available …

… propose a machine learning-based method that provides available bandwidth estimates
accurately … We evaluate our technique in controlled experimental setups in a network testbed …

… a machine learning-based predictive dynamic bandwidth … -DBA, to address the uplink
bandwidth contention and latency … the uplink bandwidth demand of each ONU-AP to be estimated. …

… As the rest of the ML techniques reviewed here are supervised learning based, for
consistency, we consider the technical details of $k{\rm NN}$ when a training set is provided. …

… CONCLUSION We developed a machine learning-based in-band OSNR estimator,
relying on GP or SVM models. We evaluated its estimation accuracy with experimental and …

… an experimental investigation of a machine learning (ML) … to an array of attack methods which
exploit different mechanisms … , we apply ML techniques to experimental data obtained from …

… In our numerical evaluation, the proposed integrated method achieves savings in spectrum
occupation up to 30% (around 20% on average) compared to traditional ILP-based RSA …

… experimental comparison study between optimized GN-model-based analytical models and
the ANN-based ML models for QoT estimation … adopt a transfer-learning-based approach, as …

… framework is experimentally evaluated through simulation experiments. The … throughput
than conventional static allocation methods and state-of-the-art bandwidth allocation techniques. …