We evaluate the performance of two domain adaptation approaches for machine learning assisted quality of transmission estimation of an optical lightpath, for a fixed/variable number of available training samples from the source/target domain
Producción CientíficaWe propose and compare a number of machine learning models to classify unestabl...
This paper proposes an evolutionary transfer learning approach (Evol-TL) for scalable quality-of-tra...
The key-operation to enabling an effective data transport abstraction in open optical line systems (...
5siMachine learning (ML) is currently being investigated as an emerging technique to automate qualit...
We compare the level of accuracy achieved by active learning and domain adaptation approaches for qu...
Estimating the quality of transmission (QoT) of a candidate lightpath prior to its establishment is ...
Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of cap...
International audienceEstimating the Quality of Transmission (QoT) of the optical signal from source...
We propose the use of machine-learning based regression model to predict the quality of transmission...
Machine Learning (ML) is becoming an integral part of Quality-of-Transmission (QoT) estimation frame...
The quality of transmission (QoT) estimation of lightpaths (LPs) has both technological and economic...
Estimating the quality of transmission (QoT) of a lightpath before its establishment is a critical p...
Planning tools with excellent accuracy along with precise and advance estimation of the quality of t...
With the advancement in evolving concepts of software-defined networks and elastic-optical-network, ...
In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intra...
Producción CientíficaWe propose and compare a number of machine learning models to classify unestabl...
This paper proposes an evolutionary transfer learning approach (Evol-TL) for scalable quality-of-tra...
The key-operation to enabling an effective data transport abstraction in open optical line systems (...
5siMachine learning (ML) is currently being investigated as an emerging technique to automate qualit...
We compare the level of accuracy achieved by active learning and domain adaptation approaches for qu...
Estimating the quality of transmission (QoT) of a candidate lightpath prior to its establishment is ...
Predicting the quality of transmission (QoT) of a lightpath prior to its deployment is a step of cap...
International audienceEstimating the Quality of Transmission (QoT) of the optical signal from source...
We propose the use of machine-learning based regression model to predict the quality of transmission...
Machine Learning (ML) is becoming an integral part of Quality-of-Transmission (QoT) estimation frame...
The quality of transmission (QoT) estimation of lightpaths (LPs) has both technological and economic...
Estimating the quality of transmission (QoT) of a lightpath before its establishment is a critical p...
Planning tools with excellent accuracy along with precise and advance estimation of the quality of t...
With the advancement in evolving concepts of software-defined networks and elastic-optical-network, ...
In multi-domain elastic optical networks with alien wavelengths, each domain needs to consider intra...
Producción CientíficaWe propose and compare a number of machine learning models to classify unestabl...
This paper proposes an evolutionary transfer learning approach (Evol-TL) for scalable quality-of-tra...
The key-operation to enabling an effective data transport abstraction in open optical line systems (...
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