19 citations · 58 across the 10 of their papers we have counts for
6 papers · 1 filter
Learning from Imperfect Annotations
Emmanouil Antonios Platanios, Maruan Al-Shedivat, Eric Xing +1
Many machine learning systems today are trained on large amounts of human-annotated data. Data annotation tasks that require a high level of competency make data acquisition expens…
Jelly Bean World: A Testbed for Never-Ending Learning
Emmanouil Antonios Platanios, Abulhair Saparov, Tom Mitchell
Machine learning has shown growing success in recent years. However, current machine learning systems are highly specialized, trained for particular problems or domains, and typica…
Agreement-based Learning
Emmanouil Antonios Platanios
Model selection is a problem that has occupied machine learning researchers for a long time. Recently, its importance has become evident through applications in deep learning. We p…
Deep Graphs
Emmanouil Antonios Platanios, Alex Smola
We propose an algorithm for deep learning on networks and graphs. It relies on the notion that many graph algorithms, such as PageRank, Weisfeiler-Lehman, or Message Passing can be…
Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach
Emmanouil A. Platanios, Hoifung Poon, Tom M. Mitchell +1
We propose an efficient method to estimate the accuracy of classifiers using only unlabeled data. We consider a setting with multiple classification problems where the target class…
Mixture Gaussian Process Conditional Heteroscedasticity
Emmanouil A. Platanios, Sotirios P. Chatzis
Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in f…