KDD

MinJoin: Efficient Edit Similarity Joins via Local Hash Minima

Haoyu Zhang, Qin Zhang

Comments Accepted to KDD 2019, full version, 22 pages

Paper Matching with Local Fairness Constraints

Ari Kobren, Barna Saha, Andrew McCallum

Comments Appears at KDD 2019 Research Track, 20 pages

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels

Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

Comments Accepted by KDD 2019

MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

Hao Wang, Tong Xu, Qi Liu, Defu Lian, Enhong Chen, Dongfang Du, Han Wu, Wen Su

Comments Accepted by KDD 2019 Research Track. In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'19)

Transcribing Content from Structural Images with Spotlight Mechanism

Yu Yin, Zhenya Huang, Enhong Chen, Qi Liu, Fuzheng Zhang, Xing Xie, Guoping Hu

Comments Accepted by KDD2018 Research Track. In proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18)

Dual Averaging Method for Online Graph-structured Sparsity

Baojian Zhou, Feng Chen, Yiming Ying

Comments 11 pages, 14 figures

Journal ref The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '19), August 4--8, 2019

Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Madelon Hulsebos, Kevin Hu, Michiel Bakker, Emanuel Zgraggen, Arvind Satyanarayan, Tim Kraska, Çağatay Demiralp, César Hidalgo

Comments KDD'19

Unsupervised Clinical Language Translation

Wei-Hung Weng, Yu-An Chung, Peter Szolovits

Comments Accepted to KDD 2019

Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction

Qi Pi, Weijie Bian, Guorui Zhou, Xiaoqiang Zhu, Kun Gai

Comments 9 pages. Accepted by KDD 2019

Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition

Anil R. Yelundur, Vineet Chaoji, Bamdev Mishra

Comments Accepted to the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2019. Contains supplementary material. arXiv admin note: text overlap with arXiv:1804.03836

Enhancing Domain Word Embedding via Latent Semantic Imputation

Shibo Yao, Dantong Yu, Keli Xiao

Comments ACM SIGKDD 2019

A Unified Framework for Marketing Budget Allocation

Kui Zhao, Junhao Hua, Ling Yan, Qi Zhang, Huan Xu, Cheng Yang

Comments KDD'19, 11 pages, 8 figures

Exploring Bias in GAN-based Data Augmentation for Small Samples

Mengxiao Hu, Jinlong Li

Comments rejected by SIGKDD 2019

A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Bang Liu, Weidong Guo, Di Niu, Chaoyue Wang, Shunnan Xu, Jinghong Lin, Kunfeng Lai, Yu Xu

Comments Accepted by KDD 2019

POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

Wen Chen, Pipei Huang, Jiaming Xu, Xin Guo, Cheng Guo, Fei Sun, Chao Li, Andreas Pfadler, Huan Zhao, Binqiang Zhao

Comments Till appear in KDD 2019

Representation Learning for Attributed Multiplex Heterogeneous Network

Yukuo Cen, Xu Zou, Jianwei Zhang, Hongxia Yang, Jingren Zhou, Jie Tang

Comments Accepted to KDD 2019. Website: https://sites.google.com/view/gatne

Short and Long-term Pattern Discovery Over Large-Scale Geo-Spatiotemporal Data

Sobhan Moosavi, Mohammad Hossein Samavatian, Arnab Nandi, Srinivasan Parthasarathy, Rajiv Ramnath

Comments In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Pairwise Comparisons with Flexible Time-Dynamics

Lucas Maystre, Victor Kristof, Matthias Grossglauser

Comments Accepted at KDD 2019

TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf

Comments KDD 2019

Exact-K Recommendation via Maximal Clique Optimization

Yu Gong, Yu Zhu, Lu Duan, Qingwen Liu, Ziyu Guan, Fei Sun, Wenwu Ou, Kenny Q. Zhu

Comments SIGKDD 2019

Stability and Generalization of Graph Convolutional Neural Networks

Saurabh Verma, Zhi-Li Zhang

Comments Accepted at The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019)

The Secret Lives of Names? Name Embeddings from Social Media

Junting Ye, Steven Skiena

Comments 9 pages; accepted to 2019 ACM SIGKDD; dataset sharing: www.name-prism.com;

Deep Landscape Forecasting for Real-time Bidding Advertising

Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang, Weinan Zhang, Yong Yu

Comments KDD 2019. The reproducible code and dataset link is https://github.com/rk2900/DLF

Predicting Economic Development using Geolocated Wikipedia Articles

Evan Sheehan, Chenlin Meng, Matthew Tan, Burak Uzkent, Neal Jean, David Lobell, Marshall Burke, Stefano Ermon

Comments Accepted to KDD 2019

MediaRank: Computational Ranking of Online News Sources

Junting Ye, Steven Skiena

Comments 9 pages. Demo: www.media-rank.com. Accepted to 2019 ACM SIGKDD

Coresets for Minimum Enclosing Balls over Sliding Windows

Yanhao Wang, Yuchen Li, Kian-Lee Tan

Comments 28 pages, 10 figures, to appear in The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '19)

Mining Subjectively Interesting Attributed Subgraphs

Anes Bendimerad, Ahmad Mel, Jefrey Lijffijt, Marc Plantevit, Céline Robardet, Tijl De Bie

Comments International Workshop On Mining And Learning With Graphs, held with SIGKDD 2018

Adversarial Variational Embedding for Robust Semi-supervised Learning

Xiang Zhang, Lina Yao, Feng Yuan

Comments 9 pages, Accepted by Research Track in KDD 2019

Adversarially Robust Submodular Maximization under Knapsack Constraints

Dmitrii Avdiukhin, Slobodan Mitrović, Grigory Yaroslavtsev, Samson Zhou

Comments To appear in KDD 2019

Smoothed Dilated Convolutions for Improved Dense Prediction

Zhengyang Wang, Shuiwang Ji

Comments The original version was accepted by KDD2018. Code is publicly available at https://github.com/divelab/dilated

Journal ref In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 2486-2495). 2018