KDD

Ultrahyperbolic Knowledge Graph Embeddings

Bo Xiong, Shichao Zhu, Mojtaba Nayyeri, Chengjin Xu, Shirui Pan, Chuan Zhou, Steffen Staab

Comments Accepted to SIGKDD'22

FedWalk: Communication Efficient Federated Unsupervised Node Embedding with Differential Privacy

Qiying Pan, Yifei Zhu

Comments 10 pages, 8 figures, to be published in the Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

A Meta Reinforcement Learning Approach for Predictive Autoscaling in the Cloud

Siqiao Xue, Chao Qu, Xiaoming Shi, Cong Liao, Shiyi Zhu, Xiaoyu Tan, Lintao Ma, Shiyu Wang, Shijun Wang, Yun Hu, Lei Lei, Yangfei Zheng, Jianguo Li, James Zhang

Comments Accepted by KDD'22 Applied Research Track

Mixture of Virtual-Kernel Experts for Multi-Objective User Profile Modeling

Zhenhui Xu, Meng Zhao, Liqun Liu, Lei Xiao, Xiaopeng Zhang, Bifeng Zhang

Comments 11 pages, accepted by SIGKDD'2022

Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction

Dongjie Wang, Yanjie Fu, Kunpeng Liu, Xiaolin Li, Yan Solihin

Comments KDD 2022

AntiBenford Subgraphs: Unsupervised Anomaly Detection in Financial Networks

Tianyi Chen, Charalampos E. Tsourakakis

Comments Accepted at KDD'22

Semi-supervised Drifted Stream Learning with Short Lookback

Weijieying Ren, Pengyang Wang, Xiaolin Li, Charles E. Hughes, Yanjie Fu

Comments To appear in KDD 2022

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments

Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen

Comments Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022. arXiv admin note: text overlap with arXiv:2108.09435

MOSPAT: AutoML based Model Selection and Parameter Tuning for Time Series Anomaly Detection

Sourav Chatterjee, Rohan Bopardikar, Marius Guerard, Uttam Thakore, Xiaodong Jiang

Comments 10 pages, submitted originally to KDD'22

ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest

Paul Baltescu, Haoyu Chen, Nikil Pancha, Andrew Zhai, Jure Leskovec, Charles Rosenberg

Comments 9 pages, 5 figures

Journal ref KDD 2022

Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation

Huarui He, Jie Wang, Zhanqiu Zhang, Feng Wu

Comments Accepted to KDD 2022

HyperLogLogLog: Cardinality Estimation With One Log More

Matti Karppa, Rasmus Pagh

Comments 10 pages, 7 figures, KDD '22

Motif Prediction with Graph Neural Networks

Maciej Besta, Raphael Grob, Cesare Miglioli, Nicola Bernold, Grzegorz Kwasniewski, Gabriel Gjini, Raghavendra Kanakagiri, Saleh Ashkboos, Lukas Gianinazzi, Nikoli Dryden, Torsten Hoefler

Journal ref Proceedings of the 28th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'22), 2022

HyperAid: Denoising in hyperbolic spaces for tree-fitting and hierarchical clustering

Eli Chien, Puoya Tabaghi, Olgica Milenkovic

Comments To appear in KDD 2022

Flexible Modeling and Multitask Learning using Differentiable Tree Ensembles

Shibal Ibrahim, Hussein Hazimeh, Rahul Mazumder

Comments Accepted at SIGKDD'2022

M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems

Zeyu Cui, Jianxin Ma, Chang Zhou, Jingren Zhou, Hongxia Yang

Comments 10 pages, 8 figures, proudly rejected by KDD 2022

MetaV: A Meta-Verifier Approach to Task-Agnostic Model Fingerprinting

Xudong Pan, Yifan Yan, Mi Zhang, Min Yang

Comments To Appear in KDD'2022

Deep Learning for Prawn Farming: Forecasting and Anomaly Detection

Joel Janek Dabrowski, Ashfaqur Rahman, Andrew Hellicar, Mashud Rana, Stuart Arnold

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2022. Lecture Notes in Computer Science, vol 13282. Springer, Cham

PinnerFormer: Sequence Modeling for User Representation at Pinterest

Nikil Pancha, Andrew Zhai, Jure Leskovec, Charles Rosenberg

Comments 11 pages, 6 figures, submitted to KDD '22

IDSGAN: Generative Adversarial Networks for Attack Generation against Intrusion Detection

Zilong Lin, Yong Shi, Zhi Xue

Comments Accepted for publication in the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2022)

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2022. Lecture Notes in Computer Science, vol.13282, 2022, pp.79-91

Graph Similarity Description: How Are These Graphs Similar?

Corinna Coupette, Jilles Vreeken

Comments 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021); 9+2 pages, 9+4 figures

Are Edge Weights in Summary Graphs Useful? -- A Comparative Study

Shinhwan Kang, Kyuhan Lee, Kijung Shin

Comments To be published in the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2022)

6GCVAE: Gated Convolutional Variational Autoencoder for IPv6 Target Generation

Tianyu Cui, Gaopeng Gou, Gang Xiong

Comments The paper has been accepted at the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2020)

Lodestar: Supporting Independent Learning and Rapid Experimentation Through Data-Driven Analysis Recommendations

Deepthi Raghunandan, Zhe Cui, Kartik Krishnan, Segen Tirfe, Shenzhi Shi, Tejaswi Darshan Shrestha, Leilani Battle, Niklas Elmqvist

Comments This paper was presented as part of the workshop called Visualization in Data Science (at ACM KDD and IEEE VIS)

Discovering material information using hierarchical Reformer model on financial regulatory filings

Francois Mercier, Makesh Narsimhan

Comments KDD ML in Finance workshop 2021

Solving Price Per Unit Problem Around the World: Formulating Fact Extraction as Question Answering

Tarik Arici, Kushal Kumar, Hayreddin Çeker, Anoop S V K K Saladi, Ismail Tutar

Comments 8 pages, 2 figures, 8 tables. This work was accepted in TrueFact KDD '21 workshop

Encoding Domain Information with Sparse Priors for Inferring Explainable Latent Variables

Arber Qoku, Florian Buettner

Comments 7 pages, 9 figures, Joint KDD 2021 Health Day and 2021 KDD Workshop on Applied Data Science for Healthcare

Scaling Graph Neural Networks with Approximate PageRank

Aleksandar Bojchevski, Johannes Gasteiger, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann

Comments Published as a Conference Paper at ACM SIGKDD 2020. Author name changed from Johannes Klicpera to Johannes Gasteiger

Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility Data

Jizhou Huang, Haifeng Wang, Miao Fan, An Zhuo, Yibo Sun, Ying Li

Comments KDD 2020

Heterogeneous Federated Learning

Fuxun Yu, Weishan Zhang, Zhuwei Qin, Zirui Xu, Di Wang, Chenchen Liu, Zhi Tian, Xiang Chen

Comments Full version [Fed2: Feature-Aligned Federated Learning] accepted in KDD'2021