148 citations · 327 across the 6 of their papers we have counts for
6 papers
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
Sijia Liu, Bhavya Kailkhura, Pin-Yu Chen +3
As application demands for zeroth-order (gradient-free) optimization accelerate, the need for variance reduced and faster converging approaches is also intensifying. This paper add…
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,…
When Crowdsourcing Meets Mobile Sensing: A Social Network Perspective
Pin-Yu Chen, Shin-Ming Cheng, Pai-Shun Ting +2
Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigate…
Supervised Collective Classification for Crowdsourcing
Pin-Yu Chen, Chia-Wei Lien, Fu-Jen Chu +2
Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainl…