KDD

PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial Actions

Ehsan Gholami, Mohammad Motamedi, Ashwin Aravindakshan

Comments 10 pages, 4 figures, this is the author's version of the work. The definitive Version of Record was published in Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), August 14-18, 2022, Washington, DC, USA

Climate Impact Modelling Framework

Blair Edwards, Paolo Fraccaro, Nikola Stoyanov, Nelson Bore, Julian Kuehnert, Kommy Weldemariam, Anne Jones

Comments KDD Fragile Earth workshop 2022

Graph Rationalization with Environment-based Augmentations

Gang Liu, Tong Zhao, Jiaxin Xu, Tengfei Luo, Meng Jiang

Comments Accepted by KDD 2022

GPatch: Patching Graph Neural Networks for Cold-Start Recommendations

Hao Chen, Zefan Wang, Yue Xu, Xiao Huang, Feiran Huang

Journal ref DLP-KDD 2022

Efficient Long Sequential User Data Modeling for Click-Through Rate Prediction

Qiwei Chen, Yue Xu, Changhua Pei, Shanshan Lv, Tao Zhuang, Junfeng Ge

Journal ref DLP-KDD 2022

Multi-AI Complex Systems in Humanitarian Response

Joseph Aylett-Bullock, Miguel Luengo-Oroz

Comments 8 pages, 1 figure

Journal ref Proceedings of the 3rd KDD Workshop on Data-driven Humanitarian Mapping, 2022, Washington, DC USA

Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation

Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li

Comments Published as a KDD'22 full paper

Knowledge Graph Completion with Pre-trained Multimodal Transformer and Twins Negative Sampling

Yichi Zhang, Wen Zhang

Comments Accepted by KDD 2022 Undergraduate Consortium

On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs

Hejie Cui, Zijie Lu, Pan Li, Carl Yang

Comments Accepted to CIKM 2022. The previous version is accepted for KDD-DLG Workshop 2021 (spotlight, no proceedings)

Ensemble of Pre-Trained Neural Networks for Segmentation and Quality Detection of Transmission Electron Microscopy Images

Arun Baskaran, Yulin Lin, Jianguo Wen, Maria K. Y. Chan

Comments 10 pages, 6 figures. Published as part of the Workshop on Machine Learning for Materials Science in conjunction with 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

A Brief History of Recommender Systems

Zhenhua Dong, Zhe Wang, Jun Xu, Ruiming Tang, Jirong Wen

Journal ref DLP-KDD 2022

TwHIN: Embedding the Twitter Heterogeneous Information Network for Personalized Recommendation

Ahmed El-Kishky, Thomas Markovich, Serim Park, Chetan Verma, Baekjin Kim, Ramy Eskander, Yury Malkov, Frank Portman, Sofía Samaniego, Ying Xiao, Aria Haghighi

Journal ref Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2022)

BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence

Isha Hameed, Samuel Sharpe, Daniel Barcklow, Justin Au-Yeung, Sahil Verma, Jocelyn Huang, Brian Barr, C. Bayan Bruss

Comments 6 pages, accepted by the KDD 2022 Workshop on Machine Learning for Finance (KDD MLF 2022)

Associative Learning for Network Embedding

Yuchen Liang, Dmitry Krotov, Mohammed J. Zaki

Comments Accepted at the Eighth International Workshop on Deep Learning on Graphs: Methods and Applications (DLG-KDD 2022), Washington DC

Identifying and Overcoming Transformation Bias in Forecasting Models

Sushant More

Comments KDD 2022 Workshop on Mining and Learning from Time Series -- Deep Forecasting: Models, Interpretability, and Applications (accepted as a poster)

On the Relationship Between Counterfactual Explainer and Recommender

Gang Liu, Zhihan Zhang, Zheng Ning, Meng Jiang

Comments Accepted by KDD 2022 Workshop on Data Science and Artificial Intelligence for Responsible Recommendations (DS4RRS)

ProActive: Self-Attentive Temporal Point Process Flows for Activity Sequences

Vinayak Gupta, Srikanta Bedathur

Comments KDD 2022

Shapelet-Based Counterfactual Explanations for Multivariate Time Series

Omar Bahri, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi

Comments Appeared in ACM SIGKDD Workshop on Mining and Learning from Time Series (KDD-MiLeTS 2022)

DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis

Birgit Pfitzmann, Christoph Auer, Michele Dolfi, Ahmed S Nassar, Peter W J Staar

Comments 9 pages, 6 figures, 5 tables. Accepted paper at SIGKDD 2022 conference

Deep Representations for Time-varying Brain Datasets

Sikun Lin, Shuyun Tang, Scott Grafton, Ambuj Singh

Journal ref ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022

Mask and Reason: Pre-Training Knowledge Graph Transformers for Complex Logical Queries

Xiao Liu, Shiyu Zhao, Kai Su, Yukuo Cen, Jiezhong Qiu, Mengdi Zhang, Wei Wu, Yuxiao Dong, Jie Tang

Comments kgTransformer; Accepted to KDD 2022

Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks

Dingyi Zhuang, Shenhao Wang, Haris N. Koutsopoulos, Jinhua Zhao

Comments Accepted by KDD 2022

Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting

Zezhi Shao, Zhao Zhang, Fei Wang, Yongjun Xu

Comments Accepted by SIGKDD 2022 (Research Track)

ROLAND: Graph Learning Framework for Dynamic Graphs

Jiaxuan You, Tianyu Du, Jure Leskovec

Comments Published in SIGKDD 2022 (Research Track)

Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space

Yu Sha, Johannes Faber, Shuiping Gou, Bo Liu, Wei Li, Stefan Schramm, Horst Stoecker, Thomas Steckenreiter, Domagoj Vnucec, Nadine Wetzstein, Andreas Widl, Kai Zhou

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

AutoShard: Automated Embedding Table Sharding for Recommender Systems

Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu

Comments Accepted by KDD 2022. Code available at https://github.com/daochenzha/autoshard

Promotheus: An End-to-End Machine Learning Framework for Optimizing Markdown in Online Fashion E-commerce

Eleanor Loh, Jalaj Khandelwal, Brian Regan, Duncan A. Little

Comments 11 pages; Accepted at KDD 2022

Connecting Low-Loss Subspace for Personalized Federated Learning

Seok-Ju Hahn, Minwoo Jeong, Junghye Lee

Comments Appears at ACM SIGKDD 2022. Code available at http://github.com/vaseline555/SuPerFed

Robust Scenario Interpretation from Multi-model Prediction Efforts

Yuanhao Lu, Ajitesh Srivastava

Comments 8 pages, 5 figures. Accepted at the 28th SIGKDD Conference on Knowledge Discovery and Data Mining (Undergraduate Consortium)

Multi-Task Fusion via Reinforcement Learning for Long-Term User Satisfaction in Recommender Systems

Qihua Zhang, Junning Liu, Yuzhuo Dai, Yiyan Qi, Yifan Yuan, Kunlun Zheng, Fan Huang, Xianfeng Tan

Comments This paper has been accepted by SIGKDD 2022