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Found 5 papers, 0 papers with code
Automatic Discovery of Multi-perspective Process Model using Reinforcement Learning
Process mining is a methodology for the derivation and analysis of process models based on the event log.
CRU: A Novel Neural Architecture for Improving the Predictive Performance of Time-Series Data
However, because this approach is learned in an independent model for each component, it cannot learn the relationships between time-series components.
Angular triangle distance for ordinal metric learning
Moreover, we also demonstrate that our proposed method outperforms the state-of-the-art ordinal metric learning method.
Metric Learning as a Service with Covariance Embedding
With the emergence of deep learning, metric learning has gained significant popularity in numerous machine learning tasks dealing with complex and large-scale datasets, such as information retrieval, object recognition and recommendation systems.
Semi-supervised binary classification with latent distance learning
In this study, we demonstrate that the stochastic data augmentation technique is less suitable for solving typical BC problems because it can omit crucial features that strictly distinguish between positive and negative samples.
