KDD

Predicting Temporal Sets with Deep Neural Networks

Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Hui Xiong, Weifeng Lv

Comments 9 pages, 6 figures, Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '2020)

PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest

Aditya Pal, Chantat Eksombatchai, Yitong Zhou, Bo Zhao, Charles Rosenberg, Jure Leskovec

Comments 10 pages, 7 figures

Journal ref KDD 2020

Unsupervised Differentiable Multi-aspect Network Embedding

Chanyoung Park, Carl Yang, Qi Zhu, Donghyun Kim, Hwanjo Yu, Jiawei Han

Comments KDD 2020 (Research Track). 9 Pages + Appendix (2 Pages). Source code can be found https://github.com/pcy1302/asp2vec. Typo fixed in Fig.2

Block Model Guided Unsupervised Feature Selection

Zilong Bai, Hoa Nguyen, Ian Davidson

Comments Published at KDD2020

Journal ref Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2020)

Lale: Consistent Automated Machine Learning

Guillaume Baudart, Martin Hirzel, Kiran Kate, Parikshit Ram, Avraham Shinnar

Comments KDD Workshop on Automation in Machine Learning (AutoML@KDD), August 2020

Adaptive Graph Encoder for Attributed Graph Embedding

Ganqu Cui, Jie Zhou, Cheng Yang, Zhiyuan Liu

Comments To appear in KDD 2020

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

Bin Liu, Chenxu Zhu, Guilin Li, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu

Comments KDD 2020 ADS track oral accepted

Laplacian Change Point Detection for Dynamic Graphs

Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany

Comments in KDD 2020, 10 pages

BusTr: Predicting Bus Travel Times from Real-Time Traffic

Richard Barnes, Senaka Buthpitiya, James Cook, Alex Fabrikant, Andrew Tomkins, Fangzhou Xu

Comments 14 pages, 2 figures, 5 tables. Citation: "Richard Barnes, Senaka Buthpitiya, James Cook, Alex Fabrikant, Andrew Tomkins, Fangzhou Xu (2020). BusTr: Predicting Bus Travel Times from Real-Time Traffic. 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. doi: 10.1145/3394486.3403376"

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training

Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang

Comments 11 pages, 5 figures, to appear in KDD 2020 proceedings

Multi-sided Exposure Bias in Recommendation

Himan Abdollahpouri, Masoud Mansoury

Comments Accepted at the International Workshop on Industrial Recommendation Systems (IRS2020) in Conjunction with ACM KDD 2020

An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph

Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola

Comments KDD 2020

Interactive Path Reasoning on Graph for Conversational Recommendation

Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, Tat-Seng Chua

Comments KDD 2020, 11 pages, 6 figures

Rapid Response Crop Maps in Data Sparse Regions

Hannah Kerner, Gabriel Tseng, Inbal Becker-Reshef, Catherine Nakalembe, Brian Barker, Blake Munshell, Madhava Paliyam, Mehdi Hosseini

Comments Presented at KDD 2020 Humanitarian Mapping Workshop

Bootstrapping Complete The Look at Pinterest

Eileen Li, Eric Kim, Andrew Zhai, Josh Beal, Kunlong Gu

Comments 9 pages, 12 figures, To be published in KDD '20

Cracking the Black Box: Distilling Deep Sports Analytics

Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu

Comments Accepted by the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020); Added the tenth feature to Table 3 for soccer;

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision

Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang

Comments Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '20)

GPT-GNN: Generative Pre-Training of Graph Neural Networks

Ziniu Hu, Yuxiao Dong, Kuansan Wang, Kai-Wei Chang, Yizhou Sun

Comments Published on KDD 2020

Mining Persistent Activity in Continually Evolving Networks

Caleb Belth, Xinyi Zheng, Danai Koutra

Comments 9 pages, plus 2 pages of supplementary material. Accepted at KDD 2020

Mapping the South African health landscape in response to COVID-19

Nompumelelo Mtsweni, Herkulaas MvE Combrink, Vukosi Marivate

Comments Accepted for KDD 2020 Workshop on Humanitarian Mapping

Graph Structure Learning for Robust Graph Neural Networks

Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang

Comments Accepted by KDD 2020

Policy-GNN: Aggregation Optimization for Graph Neural Networks

Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu

Comments Accepted by ACM SIGKDD'20 research track

CoronaSurveys: Using Surveys with Indirect Reporting to Estimate the Incidence and Evolution of Epidemics

Oluwasegun Ojo, Augusto García-Agundez, Benjamin Girault, Harold Hernández, Elisa Cabana, Amanda García-García, Payman Arabshahi, Carlos Baquero, Paolo Casari, Ednaldo José Ferreira, Davide Frey, Chryssis Georgiou, Mathieu Goessens, Anna Ishchenko, Ernesto Jiménez, Oleksiy Kebkal, Rosa Lillo, Raquel Menezes, Nicolas Nicolaou, Antonio Ortega, Paul Patras, Julian C Roberts, Efstathios Stavrakis, Yuichi Tanaka, Antonio Fernández Anta

Comments Presented at The KDD Workshop on Humanitarian Mapping, San Diego, California USA, August 24, 2020

Case study: Mapping potential informal settlements areas in Tegucigalpa with machine learning to plan ground survey

Federico Bayle, Damian E. Silvani

Comments 4 pages, 2 figures, submitted to ACM SIGKDD 2020 Conference on Knowledge Discovery and Data Mining

Fair navigation planning: a humanitarian robot use case

Martim Brandao

Comments Appeared at the KDD 2020 Workshop on Humanitarian Mapping

Understanding Negative Sampling in Graph Representation Learning

Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, Jie Tang

Comments KDD 2020

Comprehensive Information Integration Modeling Framework for Video Titling

Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Tan Jiang, Jingren Zhou, Hongxia Yang, Fei Wu

Comments 11 pages, 6 figures, to appear in KDD 2020 proceedings

Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks

Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian

Comments Accepted at KDD 2020; The first two authors contributed equally

AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types

Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han

Comments KDD 2020

Personalized PageRank to a Target Node, Revisited

Hanzhi Wang, Zhewei Wei, Junhao Gan, Sibo Wang, Zengfeng Huang

Comments ACM SIGKDD 2020