Titlebook: Machine Learning and Knowledge Discovery in Databases. Research Track; European Conference, Nuria Oliver,Fernando Pérez-Cruz,Jose A. Lozano

obsession

CHOKE

Midpoint Regularization: From High Uncertainty Training Labels to?Conservative Classification Decisiple the LS strategy smooths the one-hot encoded training signal by distributing its distribution mass over the non-ground truth classes. We extend this technique by considering example pairs, coined PLS. PLS first creates midpoint samples by averaging random sample pairs and then learns a smoothing

大廳

Charitable

precede

Gleason-score

正式通知

Certification of Model Robustness in Active Class Selection this freedom can improve the model performance and decrease the data acquisition cost, it also puts the practical value of the trained model into question: is this model really appropriate for the class proportions that are handled during deployment? What if the deployment class proportions are unc

桶去微染

GraphAnoGAN: Detecting Anomalous Snapshots from Attributed Graphsl-world networks show that GraphAnoGAN outperforms 6 baselines with a significant margin (. and . higher precision and recall, respectively compared to the best baseline, averaged across all datasets).

共棲

男生如果明白

Disparity Between Batches as a Signal for Early Stoppingr than the validation data. Furthermore, we show in a wide range of experimental settings that gradient disparity is strongly related to the generalization error between the training and test sets, and that it is also very informative about the level of label noise.