output
20162019
most citedNeural Rating Regression with Abstractive Tips Generation for Recommendation

306 citations

10 papers

cs.IR20191 cited

Deep Social Collaborative Filtering

Wenqi Fan, Yao Ma, Dawei Yin +3

Recommender systems are crucial to alleviate the information overload problem in online worlds. Most of the modern recommender systems capture users' preference towards items via t…

cs.LG2019

Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

Zhibin Li, Jian Zhang, Qiang Wu +3

Railway points are among the key components of railway infrastructure. As a part of signal equipment, points control the routes of trains at railway junctions, having a significant…

cs.LG201911 cited

Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss

Pengcheng Li, Jinfeng Yi, Bowen Zhou +1

Recent studies have highlighted that deep neural networks (DNNs) are vulnerable to adversarial examples. In this paper, we improve the robustness of DNNs by utilizing techniques of…

cs.CV201953 cited

Group Re-Identification with Multi-grained Matching and Integration

Weiyao Lin, Yuxi Li, Hao Xiao +5

The task of re-identifying groups of people underdifferent camera views is an important yet less-studied problem.Group re-identification (Re-ID) is a very challenging task sinceit…

cs.CV2019

Everyone is a Cartoonist: Selfie Cartoonization with Attentive Adversarial Networks

Xinyu Li, Wei Zhang, Tong Shen +1

Selfie and cartoon are two popular artistic forms that are widely presented in our daily life. Despite the great progress in image translation/stylization, few techniques focus spe…

cs.IR20183 cited

Etymo: A New Discovery Engine for AI Research

Weijian Zhang, Jonathan Deakin, Nicholas J. Higham +1

We present Etymo (https://etymo.io), a discovery engine to facilitate artificial intelligence (AI) research and development. It aims to help readers navigate a large number of AI-r…