KDD

Reinforced Epidemic Control: Saving Both Lives and Economy

Sirui Song, Zefang Zong, Yong Li, Xue Liu, Yang Yu

Comments Accepted by KDD'20 "AI For Covid-19" Initiative

Adversarial Infidelity Learning for Model Interpretation

Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang

Comments 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '20), August 23--27, 2020, Virtual Event, USA

Controllable Multi-Interest Framework for Recommendation

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

Comments Accepted to KDD 2020

Embedding-based Retrieval in Facebook Search

Jui-Ting Huang, Ashish Sharma, Shuying Sun, Li Xia, David Zhang, Philip Pronin, Janani Padmanabhan, Giuseppe Ottaviano, Linjun Yang

Comments 9 pages, 3 figures, 3 tables, to be published in KDD '20

Improving Robustness on Seasonality-Heavy Multivariate Time Series Anomaly Detection

Farzaneh Khoshnevisan, Zhewen Fan, Vitor R. Carvalho

Comments arXiv admin note: substantial text overlap with arXiv:1911.07104

Journal ref KDD Workshop on Mining and Learning from Time Series, 2020

A Large-Scale Analysis of Attacker Activity in Compromised Enterprise Accounts

Neil Shah, Grant Ho, Marco Schweighauser, M. H. Afifi, Asaf Cidon, David Wagner

Comments Extended report of workshop paper presented at the 1st MLHat Workshop (MLHat Security and ML 2020). KDD, 2020

On using Product-Specific Schema.org from Web Data Commons: An Empirical Set of Best Practices

Ravi Kiran Selvam, Mayank Kejriwal

Comments 8 pages, 3 tables, 6 figures, published in Workshop on Knowledge Graphs and E-Commerce at KDD 2020 (non-archival)

Uncovering socioeconomic gaps in mobility reduction during the COVID-19 pandemic using location data

Samuel P. Fraiberger, Pablo Astudillo, Lorenzo Candeago, Alex Chunet, Nicholas K. W. Jones, Maham Faisal Khan, Bruno Lepri, Nancy Lozano Gracia, Lorenzo Lucchini, Emanuele Massaro, Aleister Montfort

Comments to appear in KDD 2020, Workshop on Humanitarian Mapping

FedCD: Improving Performance in non-IID Federated Learning

Kavya Kopparapu, Eric Lin, Jessica Zhao

Comments Accepted for Oral Presentation at ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020) International workshop on Artificial Intelligence of Things

Improved Slice-wise Tumour Detection in Brain MRIs by Computing Dissimilarities between Latent Representations

Alexandra-Ioana Albu, Alina Enescu, Luigi Malagò

Comments In 2020 KDD Workshop on Applied Data Science for Healthcare, August 24, 2020, San Diego, CA, USA. ACM, New York, NY, USA, 4 pages

Impact of Medical Data Imprecision on Learning Results

Mei Wang, Jianwen Su, Haiqin Lu

Comments 2020 KDD Workshop on Applied Data Science for Healthcare

User-driven Analysis of Longitudinal Health Data with Hidden Markov Models for Clinical Insights

Bum Chul Kwon

Comments Demo presented in KDD 2020 Workshop on Applied Data Science for Healthcare

Context-Aware Attentive Knowledge Tracing

Aritra Ghosh, Neil Heffernan, Andrew S. Lan

Comments Published in KDD 2020

Clinical Recommender System: Predicting Medical Specialty Diagnostic Choices with Neural Network Ensembles

Morteza Noshad, Ivana Jankovic, Jonathan H. Chen

Comments Proceedings of 2020 KDD Workshop onApplied Data Science for Healthcare (KDD 2020).ACM

Grale: Designing Networks for Graph Learning

Jonathan Halcrow, Alexandru Moşoi, Sam Ruth, Bryan Perozzi

Comments 10 pages, 6 figures, to be published in KDD'20

Garment Design with Generative Adversarial Networks

Chenxi Yuan, Mohsen Moghaddam

Comments AdvML 2020, KDD workshop

Visualizing Deep Graph Generative Models for Drug Discovery

Karan Yang, Chengxi Zang, Fei Wang

Comments 4 pages, 2020 KDD Workshop on Applied Data Science for Healthcare

Coronavirus Knowledge Graph: A Case Study

Chongyan Chen, Islam Akef Ebeid, Yi Bu, Ying Ding

Comments 8 pages; Accepted by ACM KDD 2020

Kernel Assisted Learning for Personalized Dose Finding

Liangyu Zhu, Wenbin Lu, Michael R. Kosorok, Rui Song

Comments Accepted for KDD 2020

Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding

Yu Meng, Yunyi Zhang, Jiaxin Huang, Yu Zhang, Chao Zhang, Jiawei Han

Comments KDD 2020 Research Track. (Code: https://github.com/yumeng5/JoSH)

Breaking Moravec's Paradox: Visual-Based Distribution in Smart Fashion Retail

Shin Woong Sung, Hyunsuk Baek, Hyeonjun Sim, Eun Hie Kim, Hyunwoo Hwangbo, Young Jae Jang

Comments 10 pages, 19 figures, The fifth international workshop on fashion and KDD, KDD 2020

Emoji Prediction: Extensions and Benchmarking

Weicheng Ma, Ruibo Liu, Lili Wang, Soroush Vosoughi

Comments In Proceedings of the 9th KDD Workshop on Issues of Sentiment Discovery and Opinion Mining (WISDOM 20). San Diego, CA, USA, 7 pages

Generic Outlier Detection in Multi-Armed Bandit

Yikun Ban, Jingrui He

Comments Published in SIGKDD 2020

Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine

Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma, Hui Xiong

Journal ref KDD 2020 applied data science track

Semi-supervised Collaborative Filtering by Text-enhanced Domain Adaptation

Wenhui Yu, Xiao Lin, Junfeng Ge, Wenwu Ou, Zheng Qin

Comments KDD 2020 paper

Aligning Superhuman AI with Human Behavior: Chess as a Model System

Reid McIlroy-Young, Siddhartha Sen, Jon Kleinberg, Ashton Anderson

Comments 11 pages, 11 figure, Proceedings of the 25th ACM SIGKDD international conference on Knowledge discovery and data mining, Virtual 2020

Identifying Meaningful Indirect Indicators of Migration for Different Conflicts

Lisa Singh, Katharine Donato, Ali Arab, Tomas Alvarez Belon, Abraham Fraifeld, Sean Fulmer, Douglas Post, Yanchen Wang

Comments 3 pages ACM Humanitarian Workshop - KDD 2020

M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems

Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-ming Wu

Comments Accepted by KDD 2020 ads track as an oral paper. Code address:https://github.com/99731/M2GRL

Estimating Properties of Social Networks via Random Walk considering Private Nodes

Kazuki Nakajima, Kazuyuki Shudo

Comments 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)

Product age based demand forecast model for fashion retail

Rajesh Kumar Vashishtha, Vibhati Burman, Rajan Kumar, Srividhya Sethuraman, Abhinaya R Sekar, Sharadha Ramanan

Comments Accepted in KDD 2020 workshop , AI for fashion supply chain. accepted-list" target="_blank" rel="noopener">https://kddfashion2020.mybluemix.net/#accepted-list