28 citations · 86 across the 11 of their papers we have counts for
11 papers
Connecting First and Second Order Recurrent Networks with Deterministic Finite Automata
Qinglong Wang, Kaixuan Zhang, Xue Liu +1
We propose an approach that connects recurrent networks with different orders of hidden interaction with regular grammars of different levels of complexity. We argue that the corre…
Shapley Homology: Topological Analysis of Sample Influence for Neural Networks
Kaixuan Zhang, Qinglong Wang, Xue Liu +1
Data samples collected for training machine learning models are typically assumed to be independent and identically distributed (iid). Recent research has demonstrated that this as…
Gated Attentive-Autoencoder for Content-Aware Recommendation
Chen Ma, Peng Kang, Bin Wu +2
The rapid growth of Internet services and mobile devices provides an excellent opportunity to satisfy the strong demand for the personalized item or product recommendation. However…
Verification of Recurrent Neural Networks Through Rule Extraction
Qinglong Wang, Kaixuan Zhang, Xue Liu +1
The verification problem for neural networks is verifying whether a neural network will suffer from adversarial samples, or approximating the maximal allowed scale of adversarial p…
Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
Chen Ma, Yingxue Zhang, Qinglong Wang +1
The rapid growth of Location-based Social Networks (LBSNs) provides a great opportunity to satisfy the strong demand for personalized Point-of-Interest (POI) recommendation service…
A Comparative Study of Rule Extraction for Recurrent Neural Networks
Qinglong Wang, Kaixuan Zhang, Alexander G. Ororbia +3
Understanding recurrent networks through rule extraction has a long history. This has taken on new interests due to the need for interpreting or verifying neural networks. One basi…
An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks
Qinglong Wang, Kaixuan Zhang, Alexander G. Ororbia +3
Rule extraction from black-box models is critical in domains that require model validation before implementation, as can be the case in credit scoring and medical diagnosis. Though…
Learning Adversary-Resistant Deep Neural Networks
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
Deep neural networks (DNNs) have proven to be quite effective in a vast array of machine learning tasks, with recent examples in cyber security and autonomous vehicles. Despite the…
Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks
Qinglong Wang, Wenbo Guo, Alexander G. Ororbia +6
Deep neural networks have proven to be quite effective in a wide variety of machine learning tasks, ranging from improved speech recognition systems to advancing the development of…
Adversary Resistant Deep Neural Networks with an Application to Malware Detection
Qinglong Wang, Wenbo Guo, Kaixuan Zhang +4
Beyond its highly publicized victories in Go, there have been numerous successful applications of deep learning in information retrieval, computer vision and speech recognition. In…
Smart Charging for Electric Vehicles: A Survey From the Algorithmic Perspective
Qinglong Wang, Xue Liu, Jian Du +1
Smart interactions among the smart grid, aggregators and EVs can bring various benefits to all parties involved, e.g., improved reliability and safety for the smart gird, increased…