KDD

A Canine Census to Influence Public Policy

Matias Apa, Maria Cecilia Faini, Mohammad Aliannejadi, Maria Soledad Pera

Comments Appeared in epiDAMIK Workshop in SIGKDD

Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies

Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang

Comments Accepted by SIGKDD Explorations

SCE: Scalable Network Embedding from Sparsest Cut

Shengzhong Zhang, Zengfeng Huang, Haicang Zhou, Ziang Zhou

Comments KDD 2020

Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules

Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz

Comments Preprint version. To appear in: Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2018. See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3074 for further information. arXiv admin note: text overlap with arXiv:1812.00050

Journal ref Proc. PAKDD (1) 2018: 29-42

DeepTriage: Automated Transfer Assistance for Incidents in Cloud Services

Phuong Pham, Vivek Jain, Lukas Dauterman, Justin Ormont, Navendu Jain

Journal ref KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining August 2020. Pages 3281-3289

Towards Spatial Variability Aware Deep Neural Networks (SVANN): A Summary of Results

Jayant Gupta, Yiqun Xie, Shashi Shekhar

Comments Accepted in 1st ACM SIGKDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (Deepspatial 2020), San Diego, CA, August 24, 2020

Resource-Constrained Federated Learning with Heterogeneous Labels and Models

Gautham Krishna Gudur, Bala Shyamala Balaji, Satheesh K. Perepu

Comments 6 pages, 5 figures, ACM KDD 2020 (The 3rd International Workshop on Artificial Intelligence of Things - AIoT'20)

Opinion Dynamics with Varying Susceptibility to Persuasion via Non-Convex Local Search

Rediet Abebe, T-H. Hubert Chan, Jon Kleinberg, Zhibin Liang, David Parkes, Mauro Sozio, Charalampos E. Tsourakakis

Comments This paper is a merge of [Abebe, Kleinberg, Parkes, Tsourakakis - KDD 2018] (arXiv:1801.07863) and [Chan, Liang, Sozio - WWW 2019], and contains additional materials on the budgeted variant of the problem

Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak

Amanuel Alambo, Manas Gaur, Krishnaprasad Thirunarayan

Comments 2020 ACM SIGKDD Workshop on Knowledge-infused Mining and Learning (KiML'20)

FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging

Doyen Sahoo, Wang Hao, Shu Ke, Wu Xiongwei, Hung Le, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi

Comments Published at KDD 2019 (Applied Data Science track). Demo is accessible at https://foodai.org/

Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs

Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi

Comments KDD 2020 Submission. Our code is open-sourced at https://github.com/chaoyanghe/bipartite-graph-learning

GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction

Thai Le, Suhang Wang, Dongwon Lee

Comments Accepted at the 26th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)

FreeDOM: A Transferable Neural Architecture for Structured Information Extraction on Web Documents

Bill Yuchen Lin, Ying Sheng, Nguyen Vo, Sandeep Tata

Comments in Proc. of KDD 2020 (Research Track). Figure 5 updated

CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring

Jiaxin Huang, Yiqing Xie, Yu Meng, Yunyi Zhang, Jiawei Han

Comments KDD 2020 Research Track

Combinatorial Black-Box Optimization with Expert Advice

Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan

Journal ref KDD 2020

Deep Expectation-Maximization for Semi-Supervised Lung Cancer Screening

Sumeet Menon, David Chapman, Phuong Nguyen, Yelena Yesha, Michael Morris, Babak Saboury

Comments This paper has been accepted at the ACM SIGKDD Workshop DCCL 2019. accepted-papers" target="_blank" rel="noopener">https://sites.google.com/view/kdd-workshop-2019/accepted-papers https://drive.google.com/file/d/0B8FX-5qN3tbjM3c4SVZDYWxjbGhCekhjUV9PUC11b3dOSXRR/view

Automatic Financial Feature Construction

Jie Fang, Shutao Xia, Jianwu Lin, Yong Jiang

Comments Its final version has been accepted by KDD ML in Finance 2020

FLEN: Leveraging Field for Scalable CTR Prediction

Wenqiang Chen, Lizhang Zhan, Yuanlong Ci, Minghua Yang, Chen Lin, Dugang Liu

Comments KDD'20 DLP workshop, 9 pages

Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage Normalization

Hannah Kerner, Ritvik Sahajpal, Sergii Skakun, Inbal Becker-Reshef, Brian Barker, Mehdi Hosseini, Estefania Puricelli, Patrick Gray

Comments Presented at KDD 2020 Fragile Earth: Data Science for a Sustainable Planet Workshop

Out-Of-Bag Anomaly Detection

Egor Klevak, Sangdi Lin, Andy Martin, Ondrej Linda, Eric Ringger

Comments 13 pages, 4 figures, KDD 2020 TrueFact Workshop: Making a Credible Web for Tomorrow

Exo-SIR: An Epidemiological Model to Analyze the Impact of Exogenous Infection of COVID-19 in India

Nirmal Kumar Sivaraman, Manas Gaur, Shivansh Baijal, Ch V Radha Sai Rupesh, Sakthi Balan Muthiah, Amit Sheth

Comments 9 pages, 9 figures, Accepted at ACM KDD'20 Health Day (AI for COVID)

Leveraging traditional ecological knowledge in ecosystem restoration projects utilizing machine learning

Bogdana Rakova, Alexander Winter

Comments In Proceedings of the ACM Knowledge Discovery and Data Mining (KDD) 2020 Conference Workshop on "Fragile Earth: Data Science for a Sustainable Planet"

Navigating the landscape of COVID-19 research through literature analysis: A bird's eye view

Lana Yeganova, Rezarta Islamaj, Qingyu Chen, Robert Leaman, Alexis Allot, Chin-Hsuan Wei, Donald C. Comeau, Won Kim, Yifan Peng, W. John Wilbur, Zhiyong Lu

Comments 10 pages, 8 Figures, Submitted to KDD 2020 Health Day

Journal ref KDD 2020 Health Day: AI for COVID, August 23-27, 2020, Virtual Conference, CA, US

Machine Learning for Temporal Data in Finance: Challenges and Opportunities

Jason Wittenbach, Brian d'Alessandro, C. Bayan Bruss

Comments KDD '20 ML in Finance Workshop

Accurate and Intuitive Contextual Explanations using Linear Model Trees

Aditya Lahiri, Narayanan Unny Edakunni

Comments KDD Workshop on ML in Finance 2020

Leveraging Model Inherent Variable Importance for Stable Online Feature Selection

Johannes Haug, Martin Pawelczyk, Klaus Broelemann, Gjergji Kasneci

Comments To be published in the Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020)

Active Learning++: Incorporating Annotator's Rationale using Local Model Explanation

Bhavya Ghai, Q. Vera Liao, Yunfeng Zhang, Klaus Mueller

Comments Accepted at Workshop on Data Science with Human in the Loop (DaSH) @ ACM SIGKDD 2020

TorchKGE: Knowledge Graph Embedding in Python and PyTorch

Armand Boschin

Comments Paper presented at KDD-IWKG 2020

Learning Latent Causal Structures with a Redundant Input Neural Network

Jonathan D. Young, Bryan Andrews, Gregory F. Cooper, Xinghua Lu

Comments Proceedings of the 2020 KDD Workshop on Causal Discovery, in Proceedings of Machine Learning Research

RayS: A Ray Searching Method for Hard-label Adversarial Attack

Jinghui Chen, Quanquan Gu

Comments 9 pages, 4 figures, 9 tables. In KDD 2020