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Interpretability of deep learning models: A survey of results
Deep neural networks have achieved near-human accuracy levels in various types of
classification and prediction tasks including images, text, speech, and video data. However …
classification and prediction tasks including images, text, speech, and video data. However …
Auditing black-box models for indirect influence
Data-trained predictive models see widespread use, but for the most part they are used as
black boxes which output a prediction or score. It is therefore hard to acquire a deeper …
black boxes which output a prediction or score. It is therefore hard to acquire a deeper …
Improving the quality of explanations with local embedding perturbations
Classifier explanations have been identified as a crucial component of knowledge
discovery. Local explanations evaluate the behavior of a classifier in the vicinity of a given …
discovery. Local explanations evaluate the behavior of a classifier in the vicinity of a given …
Methods for explaining Top-N recommendations through subgroup discovery
Abstract Explainable Artificial Intelligence (XAI) has received a lot of attention over the past
decade, with the proposal of many methods explaining black box classifiers such as neural …
decade, with the proposal of many methods explaining black box classifiers such as neural …
A comparison of constant curvature forward kinematics for multisection continuum manipulators
Over the past few years, modeling of continuum robots has been the subject of considerable
attention in the research community. In this paper, we compare a set of forward kinematic …
attention in the research community. In this paper, we compare a set of forward kinematic …
Declarative aspects in explicative data mining for computational sensemaking
Computational sensemaking aims to develop methods and systems to “make sense” of
complex data and information. The ultimate goal is then to provide insights and enhance …
complex data and information. The ultimate goal is then to provide insights and enhance …
Why should i trust this item? explaining the recommendations of any model
Explainable AI has received a lot of attention over the past decade, with the proposal of
many methods explaining black box classifiers such as neural networks. Despite the …
many methods explaining black box classifiers such as neural networks. Despite the …
Exploiting patterns to explain individual predictions
Users need to understand the predictions of a classifier, especially when decisions based
on the predictions can have severe consequences. The explanation of a prediction reveals …
on the predictions can have severe consequences. The explanation of a prediction reveals …
Softmax-based classification is k-means clustering: Formal proof, consequences for adversarial attacks, and improvement through centroid based tailoring
We formally prove the connection between k-means clustering and the predictions of neural
networks based on the softmax activation layer. In existing work, this connection has been …
networks based on the softmax activation layer. In existing work, this connection has been …
Exceptionally monotone models—the rank correlation model class for exceptional model mining
Abstract Exceptional Model Mining strives to find coherent subgroups of the dataset where
multiple target attributes interact in an unusual way. One instance of such an investigated …
multiple target attributes interact in an unusual way. One instance of such an investigated …