Simplifying the Supervised Learning of Kerr Nonlinearity Compensation Algorithms by Data Augmentation.
Vladislav NeskorniukPedro J. FreireAntonio NapoliBernhard SpinnlerWolfgang SchairerJaroslaw E. PrilepskyNelson CostaSergei K. TuritsynPublished in: ECOC (2020)
Keyphrases
- data sets
- data mining algorithms
- training data
- data structure
- database
- supervised learning
- knowledge discovery
- learning algorithm
- high quality
- data analysis
- synthetic data
- data collection
- sensor data
- data points
- small number
- raw data
- data processing
- data distribution
- missing data
- training examples
- theoretical analysis
- computationally efficient
- data mining tasks
- significant improvement
- data sources
- image data
- computational complexity
- probability distribution
- noisy data
- data objects
- data reduction
- attribute values
- unsupervised learning
- optimization problems
- dimensionality reduction
- semi supervised
- wireless sensor networks
- lower bound
- feature space