KDD 2024: all accepted papers
- Harvesting Efficient On-Demand Order Pooling from Skilled Couriers: Enhancing Graph Representation Learning for Refining Real-time Many-to-One Assignments ↗Yile Liang, Jiuxia Zhao, Donghui Li et al.
- Health Day: Building Health AI Ecosystem: From Data Harmonization to Knowledge Discovery ↗Jake Y. Chen, Peipei Ping
- Hierarchical Linear Symbolized Tree-Structured Neural Processes ↗Jinyang Tai, Yike Guo
- Improved Active Covering via Density-Based Space Transformation ↗MohammadHossein Bateni, Hossein Esfandiari, Samira Hossein Ghorban et al.
- Iterative Weak Learnability and Multiclass AdaBoost ↗In‐Koo Cho, Jonathan Libgober, Cheng Ding
- KDD 2024 Finance Day ↗Guiling Wang, Daniel Borrajo
- KDD 2024 Special Day - AI for Environment ↗Karina Gibert, Wee Hyong Tok, Miquel Sànchez–Marrè
- KDD workshop on Evaluation and Trustworthiness of Generative AI Models ↗Yuan Ling, Shujing Dong, Yarong Feng et al.
- KiL 2024: 4th International Workshop on Knowledge-infused Learning (Towards Consistent, Reliable, Explainable, and Safe LLMs) ↗Manas Gaur, Efthymia Tsamoura, Edward Raff et al.
- Know in AdVance: Linear-Complexity Forecasting of Ad Campaign Performance with Evolving User Interest ↗Xiaoyu Wang, Yonghui Guo, Hui Sheng et al.
- Know, Grow, and Protect Net Worth: Using ML for Asset Protection by Preventing Overdraft Fees ↗Avishek Kumar, Tyson Silver
- Learning to Bid the Interest Rate in Online Unsecured Personal Loans ↗Dong Jun Jee, Seung Jung Jin, Ji Hoon Yoo et al.
- Leveraging Exposure Networks for Detecting Fake News Sources ↗Maor Reuben, Lisa Friedland, Rami Puzis et al.
- MGMatch: Fast Matchmaking with Nonlinear Objective and Constraints via Multimodal Deep Graph Learning ↗Yu Sun, Kai Wang, Zhipeng Hu et al.
- Machine Learning in Finance ↗Leman Akoglu, Nitesh V. Chawla, Josep Domingo‐Ferrer et al.
- Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases ↗Daoyuan Chen, Yaliang Li, Bolin Ding
- NL2Code-Reasoning and Planning with LLMs for Code Development ↗Ye Xing, Jun Huan, Wee Hyong Tok et al.
- Nested Fusion: A Method for Learning High Resolution Latent Structure of Multi-Scale Measurement Data on Mars ↗Austin P. Wright, Scott Davidoff, Duen Horng Chau
- Optimized Cost Per Click in Online Advertising: A Theoretical Analysis ↗Kaichen Zhang, Zixuan Yuan, Hui Yun Xiong
- Overview of ACM SIGKDD 2024 AI4Science4AI Special Day ↗Wei Ding, Gustau Camps‐Valls
- Representation Learning of Geometric Trees ↗Zheng Zhang, Allen Zhang, Ruth Nelson et al.
- Responsible AI Day ↗Ricardo A. Baeza-Yates, Nataly Buslón
- Robust Predictions with Ambiguous Time Delays: A Bootstrap Strategy ↗Jiajie Wang, Zhiyuan Jerry Lin, Wen Chen
- Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior ↗Pingchuan Ma, Rui Ding, Qiang Fu et al.
- Scalable Graph Learning for your Enterprise ↗Hema Raghavan
- Scaling Training Data with Lossy Image Compression ↗Katherine L. Mentzer, Andrea Montanari A
- Spatio-Temporal Consistency Enhanced Differential Network for Interpretable Indoor Temperature Prediction ↗Dekang Qi, Xiuwen Yi, Chengjie Guo et al.
- Statistical Models of Top- k Partial Orders ↗Amel Awadelkarim, Johan H. Ugander
- The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs ↗Sanjay Purushotham, Dongjin Song, Qingsong Wen et al.
- The 2nd International Workshop: From Innovation to Scale (I2S) - Successfully Build, Commercialize, and Scale AI Innovations ↗Ankur M. Teredesai, Michael Zeller, Mohak Shah et al.
- The 4th KDD Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems (DeepSpatial'24) ↗Zhe Jiang, Liang Zhao, Xun S. Zhou et al.
- The First Workshop on AI Behavioral Science ↗Himabindu Lakkaraju, Qiaozhu Mei, Chenhao Tan et al.
- The Third Workshop on Applied Machine Learning Management ↗Dmitri Goldenberg, Shir Meir Lador, Elena Sokolova et al.
- Top-Down Bayesian Posterior Sampling for Sum-Product Networks ↗Soma Yokoi, Issei Sato
- Unified Low-rank Compression Framework for Click-through Rate Prediction ↗Hao Yu, Minghao Fu, Jiandong Ding et al.
- Valuing an Engagement Surface using a Large Scale Dynamic Causal Model ↗Abhimanyu Mukerji, Sushant More, Ashwin Viswanathan Kannan et al.
- Workshop on Deep Learning and Large Language Models for Knowledge Graphs (DL4KG) ↗Mehwish Alam, Davide Buscaldi, Michael Cochez et al.
- Workshop on Discovering Drift Phenomena in Evolving Data Landscape (DELTA) ↗Marco Piangerelli, Bardh Prenkaj, Ylenia Rotalinti et al.
- epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery ↗Alexander Rodríguez, Bijaya Adhikari, Ajitesh Srivastava et al.
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