148 citations · 185 across the 4 of their papers we have counts for
5 papers
Leveraging Latent Features for Local Explanations
Ronny Luss, Pin-Yu Chen, Amit Dhurandhar +4
As the application of deep neural networks proliferates in numerous areas such as medical imaging, video surveillance, and self driving cars, the need for explaining the decisions…
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks
Chun-Chen Tu, Paishun Ting, Pin-Yu Chen +5
Recent studies have shown that adversarial examples in state-of-the-art image classifiers trained by deep neural networks (DNN) can be easily generated when the target model is tra…
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives
Amit Dhurandhar, Pin-Yu Chen, Ronny Luss +4
In this paper we propose a novel method that provides contrastive explanations justifying the classification of an input by a black box classifier such as a deep neural network. Gi…
FEAST: An Automated Feature Selection Framework for Compilation Tasks
Pai-Shun Ting, Chun-Chen Tu, Pin-Yu Chen +2
The success of the application of machine-learning techniques to compilation tasks can be largely attributed to the recent development and advancement of program characterization,…
Identifying Influential Links for Event Propagation on Twitter: A Network of Networks Approach
Pin-Yu Chen, Chun-Chen Tu, Pai-Shun Ting +3
Patterns of event propagation in online social networks provide novel insights on the modeling and analysis of information dissemination over networks and physical systems. This pa…