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The Penalty Imposed by Ablated Data Augmentation
There is a set of data augmentation techniques that ablate parts of the ...
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Attribution in Scale and Space
We study the attribution problem [28] for deep networks applied to perce...
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Estimating Training Data Influence by Tracking Gradient Descent
We introduce a method called TrackIn that computes the influence of a tr...
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The many Shapley values for model explanation
The Shapley value has become a popular method to attribute the predictio...
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A New Interaction Index inspired by the Taylor Series
We study interactions among players in cooperative games. We propose a n...
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A Note about: Local Explanation Methods for Deep Neural Networks lack Sensitivity to Parameter Values
Local explanation methods, also known as attribution methods, attribute ...
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How Important Is a Neuron?
The problem of attributing a deep network's prediction to its input/base...
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Did the Model Understand the Question?
We analyze state-of-the-art deep learning models for three tasks: questi...
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It was the training data pruning too!
We study the current best model (KDG) for question answering on tabular ...
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A Simple and Efficient MapReduce Algorithm for Data Cube Materialization
Data cube materialization is a classical database operator introduced in...
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Abductive Matching in Question Answering
We study question-answering over semi-structured data. We introduce a ne...
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Gradients of Counterfactuals
Gradients have been used to quantify feature importance in machine learn...
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