KDD

HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline

Yang Li, Xinyan Chen, Wenxuan Guo, Xijun Li, Wanqian Luo, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Junchi Yan

Comments Published at SIGKDD 2023, see http://dl.acm.org/doi/10.1145/3580305.3599837

Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids

Carmelo Ardito, Yashar Deldjoo, Tommaso Di Noia, Eugenio Di Sciascio, Fatemeh Nazary, Giovanni Servedio

Comments Accepted in AdvML@KDD'22

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

Zhikai Chen, Haitao Mao, Hang Li, Wei Jin, Hongzhi Wen, Xiaochi Wei, Shuaiqiang Wang, Dawei Yin, Wenqi Fan, Hui Liu, Jiliang Tang

Comments To be appear on SIGKDD Explorations

GroupMixNorm Layer for Learning Fair Models

Anubha Pandey, Aditi Rai, Maneet Singh, Deepak Bhatt, Tanmoy Bhowmik

Comments 12 pages, 6 figures, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2023

Leveraged Mel spectrograms using Harmonic and Percussive Components in Speech Emotion Recognition

David Hason Rudd, Huan Huo, Guandong Xu

Comments 12 pages

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2022. Lecture Notes in Computer Science(), vol 13281. Springer, Cham

An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance

David Hason Rudd, Huan Huo, Guandong Xu

Comments 12 pages

Journal ref Advances in Knowledge Discovery and Data Mining. PAKDD 2023. Lecture Notes in Computer Science(), vol 13937. Springer, Cham

All in One: Multi-task Prompting for Graph Neural Networks

Xiangguo Sun, Hong Cheng, Jia Li, Bo Liu, Jihong Guan

Comments KDD 23 Best Research Paper Award, which is the first for Hong Kong and Mainland China. A Python Library is released as ProG: https://github.com/sheldonresearch/ProG Submitted to SIGKDD'23 in 03 Feb 2023; Receive Acceptance in 17 May 2023 (Rating 3 4 4 4); Submit to arXiv 1st time in 4 Jul 2023

TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting

Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam

Comments Accepted in the Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 23), Research Track. Delayed release in arXiv to comply with the conference policies on the double-blind review process. This paper has been submitted to the KDD peer-review process on Feb 02, 2023

Discovering Dynamic Causal Space for DAG Structure Learning

Fangfu Liu, Wenchang Ma, An Zhang, Xiang Wang, Yueqi Duan, Tat-Seng Chua

Comments Accepted by KDD 2023. Our codes are available at https://github.com/liuff19/CASPER

Towards Aligned Canonical Correlation Analysis: Preliminary Formulation and Proof-of-Concept Results

Biqian Cheng, Evangelos E. Papalexakis, Jia Chen

Comments 4 pages, 7 figures, KDD SoCal symposium 2023 (extended version)

ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop

Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang

Comments Accepted by KDD 2023

Building Open Knowledge Graph for Metal-Organic Frameworks (MOF-KG): Challenges and Case Studies

Yuan An, Jane Greenberg, Xintong Zhao, Xiaohua Hu, Scott McCLellan, Alex Kalinowski, Fernando J. Uribe-Romo, Kyle Langlois, Jacob Furst, Diego A. Gómez-Gualdrón, Fernando Fajardo-Rojas, Katherine Ardila

Comments Accepted by the International Workshop on Knowledge Graphs and Open Knowledge Network (OKN'22) Co-located with the 28th ACM SIGKDD Conference

Analyzing and Predicting Low-Listenership Trends in a Large-Scale Mobile Health Program: A Preliminary Investigation

Arshika Lalan, Shresth Verma, Kumar Madhu Sudan, Amrita Mahale, Aparna Hegde, Milind Tambe, Aparna Taneja

Comments Accepted to Data Science for Social Good Workshop, KDD 2023

An In-Depth Evaluation of Federated Learning on Biomedical Natural Language Processing

Le Peng, Gaoxiang Luo, sicheng zhou, jiandong chen, Rui Zhang, Ziyue Xu, Ju Sun

Comments Accepted by KDD 2023 Workshop FL4Data-Mining

Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization

Yunze Tong, Junkun Yuan, Min Zhang, Didi Zhu, Keli Zhang, Fei Wu, Kun Kuang

Comments This paper has been accepted by KDD 2023

Spectral Clustering of Attributed Multi-relational Graphs

Ylli Sadikaj, Yllka Velaj, Sahar Behzadi, Claudia Plant

Journal ref Association for Computing Machinery, Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 21, Virtual Event, Singapore, August 2021, Pages 1431-1440

FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy

Jianqing Zhang, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Haibing Guan

Comments Accepted by KDD 2023

How Transitive Are Real-World Group Interactions? -- Measurement and Reproduction

Sunwoo Kim, Fanchen Bu, Minyoung Choe, Jaemin Yoo, Kijung Shin

Comments Published in KDD 2023. 12 pages, 7 figures, and 11 tables

Bid Optimization for Offsite Display Ad Campaigns on eCommerce

Hangjian Li, Dong Xu, Konstantin Shmakov, Kuang-Chih Lee, Wei Shen

Journal ref Workshop on Decision Intelligence and Analytics for Online Marketplaces, KDD 2023

The Missing Indicator Method: From Low to High Dimensions

Mike Van Ness, Tomas M. Bosschieter, Roberto Halpin-Gregorio, Madeleine Udell

Journal ref SIGKDD 2023 Proceedings p5004 5015

Marginal Nodes Matter: Towards Structure Fairness in Graphs

Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou

Comments SIGKDD Explorations (To Appear)

Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers

Yu Zhang, Bowen Jin, Xiusi Chen, Yanzhen Shen, Yunyi Zhang, Yu Meng, Jiawei Han

Comments 12 pages; Accepted to KDD 2023 (Code: https://github.com/yuzhimanhua/FUTEX)

DESCN: Deep Entire Space Cross Networks for Individual Treatment Effect Estimation

Kailiang Zhong, Fengtong Xiao, Yan Ren, Yaorong Liang, Wenqing Yao, Xiaofeng Yang, Ling Cen

Comments Accepted by SIGKDD 2022 Applied Data Science Track

Journal ref Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), August 14-18, 2022, Washington, DC, USA

Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation

Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang

Comments Accepted by NeurIPS 2023, Track on Datasets and Benchmarks; Dataset for KDD Cup 2023, https://kddcup23.github.io/

When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting

Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash

Comments Accepted at KDD 2023

Rethinking Financial Service Promotion With Hybrid Recommender Systems at PicPay

Gabriel Mendonça, Matheus Santos, André Gonçalves, Yan Almeida

Comments 4 pages, 4 figures, submitted to ACM KDD '23 2nd Workshop on End-End Customer Journey Optimization

Automatic Music Playlist Generation via Simulation-based Reinforcement Learning

Federico Tomasi, Joseph Cauteruccio, Surya Kanoria, Kamil Ciosek, Matteo Rinaldi, Zhenwen Dai

Comments 10 pages. KDD 23

Precursor-of-Anomaly Detection for Irregular Time Series

Sheo Yon Jhin, Jaehoon Lee, Noseong Park

Comments KDD 2023 accepted paper

DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection

Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun

Comments Accepted by ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2023)

A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain

Mayank Kejriwal, Hamid Haidarian, Min-Hsueh Chiu, Andy Xiang, Deep Shrestha, Faizan Javed

Comments Presented as an applied data science poster in KDD 2023