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Found 5 papers, 1 papers with code
Fast Text-Only Domain Adaptation of RNN-Transducer Prediction Network
In this paper we show that RNN-transducer models can be effectively adapted to new domains using only small amounts of textual data.
Interpreting Classifiers through Attribute Interactions in Datasets
In this work we present the novel ASTRID method for investigating which attribute interactions classifiers exploit when making predictions.
Multivariate Confidence Intervals
In this paper we define confidence intervals for multivariate data that extend the one-dimensional definition in a natural way.
Finding Statistically Significant Attribute Interactions
In many data exploration tasks it is meaningful to identify groups of attribute interactions that are specific to a variable of interest.
Semi-supervised Kernel Metric Learning Using Relative Comparisons
We consider the problem of metric learning subject to a set of constraints on relative-distance comparisons between the data items.
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