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stat.ML2019
Rank aggregation for non-stationary data streams
Ekhine Irurozki, Jesus Lobo, Aritz Perez +1
We consider the problem of learning over non-stationary ranking streams. The rankings can be interpreted as the preferences of a population and the non-stationarity means that the…
stat.ML2019
General Supervision via Probabilistic Transformations
Santiago Mazuelas, Aritz Perez
Different types of training data have led to numerous schemes for supervised classification. Current learning techniques are tailored to one specific scheme and cannot handle gener…