- 2023
- Vanessa Cai, Pradeep Prabakar, Manuel Serrano Rebuelta, Lucas Rosen, Federico Monti, Katarzyna Janocha, Tomo Lazovich, Jeetu Raj, Yedendra Shrinivasan, Hao Li, Thomas Markovich:
TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter. AdKDD@KDD 2023 - Sharad Chitlangia, Krishna Reddy Kesari, Rajat Agarwal:
Scaling Generative Pre-training for User Ad Activity Sequences. AdKDD@KDD 2023 - Matthew Dawson, Badih Ghazi, Pritish Kamath, Kapil Kumar, Ravi Kumar, Bo Luan, Pasin Manurangsi, Nishanth Mundru, Harikesh Nair, Adam Sealfon, Shengyu Zhu:
Optimizing Hierarchical Queries for the Attribution Reporting API. AdKDD@KDD 2023 - Carson Denison, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Krishna Giri Narra, Amer Sinha, Avinash V. Varadarajan, Chiyuan Zhang:
Private Ad Modeling with DP-SGD. AdKDD@KDD 2023 - Yueh-Ning Ku, Mikhail Kuznetsov, Shaunak Mishra, Paloma de Juan:
Staging E-Commerce Products for Online Advertising using Retrieval Assisted Image Generation. AdKDD@KDD 2023 - Phuong Ha Nguyen, Djordje Gligorijevic, Arnab Borah, Gajanan Adalinge, Abraham Bagherjeiran:
Practical Budget Pacing Algorithms and Simulation Test Bed for eBay Marketplace Sponsored Search. AdKDD@KDD 2023 - Xuewei Wang, Qiang Jin, Shengyu Huang, Min Zhang, Xi Liu, Zhengli Zhao, Yukun Chen, Zhengyu Zhang, Jiyan Yang, Ellie Wen, Sagar Chordia, Wenlin Chen, Qin Huang:
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking. AdKDD@KDD 2023 - YaChen Yan, Liubo Li:
AdaEnsemble: Learning Adaptively Sparse Structured Ensemble Network for Click-Through Rate Prediction. AdKDD@KDD 2023 - Menglin Yang, Min Zhou, Lujia Pan, Irwin King:
κHGCN: Tree-likeness Modeling via Continuous and Discrete Curvature Learning. KDD 2023: 2965-2977 - Sungwon Park, Sungwon Han, Fangzhao Wu, Sundong Kim, Bin Zhu, Xing Xie, Meeyoung Cha:
FedDefender: Client-Side Attack-Tolerant Federated Learning. KDD 2023: 1850-1861 - Da Yan, Ariful Azad, Jie Hou, Jake Y. Chen, Mohammed J. Zaki:
22nd International Workshop on Data Mining in Bioinformatics (BIOKDD 2023). KDD 2023: 5897-5898 - Atsushi Miyauchi, Tianyi Chen, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis:
Densest Diverse Subgraphs: How to Plan a Successful Cocktail Party with Diversity. KDD 2023: 1710-1721 - Federico Bianchi, Patrick John Chia, Jacopo Tagliabue, Ciro Greco, Gabriel de Souza P. Moreira, Davide Eynard, Fahd Husain, Claudio Pomo:
EvalRS 2023: Well-Rounded Recommender Systems for Real-World Deployments. KDD 2023: 5851-5852 - Anna Beer, Andrew Draganov, Ellen Hohma, Philipp Jahn, Christian M. M. Frey, Ira Assent:
Connecting the Dots - Density-Connectivity Distance unifies DBSCAN, k-Center and Spectral Clustering. KDD 2023: 80-92 - Tao Shen, Xiubo Geng, Chongyang Tao, Can Xu, Guodong Long, Kai Zhang, Daxin Jiang:
UnifieR: A Unified Retriever for Large-Scale Retrieval. KDD 2023: 4787-4799 - Yuhan Wu, Shiqi Jiang, Siyuan Dong, Zheng Zhong, Jiale Chen, Yutong Hu, Tong Yang, Steve Uhlig, Bin Cui:
MicroscopeSketch: Accurate Sliding Estimation Using Adaptive Zooming. KDD 2023: 2660-2671 - Peng Peng, Shengyi Ji, Zhen Tian, Hongbo Jiang, Weiguo Zheng, Xuecang Zhang:
Locality Sensitive Hashing for Optimizing Subgraph Query Processing in Parallel Computing Systems. KDD 2023: 1885-1896 - Haotian Wang, Kun Kuang, Haoang Chi, Longqi Yang, Mingyang Geng, Wanrong Huang, Wenjing Yang:
Treatment Effect Estimation with Adjustment Feature Selection. KDD 2023: 2290-2301 - Ping Li, Xiaoyun Li:
OPORP: One Permutation + One Random Projection. KDD 2023: 1303-1315 - Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Hongyang Chen, Yu Zheng, Roger Zimmermann:
Graph Neural Processes for Spatio-Temporal Extrapolation. KDD 2023: 752-763 - Long He, Ho-Yin Mak:
Prescriptive PCA: Dimensionality Reduction for Two-stage Stochastic Optimization. KDD 2023: 711-721 - Thomas M. McDonald, Lucas Maystre, Mounia Lalmas, Daniel Russo, Kamil Ciosek:
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay. KDD 2023: 1687-1697 - João Gama, Slawomir Nowaczyk, Sepideh Pashami, Rita P. Ribeiro, Grzegorz J. Nalepa, Bruno Veloso:
XAI for Predictive Maintenance. KDD 2023: 5798-5799 - Guangyi Zhang, Nikolaj Tatti, Aristides Gionis:
Finding Favourite Tuples on Data Streams with Provably Few Comparisons. KDD 2023: 3229-3238 - Siddharth Bhatia, Mohit Wadhwa, Kenji Kawaguchi, Neil Shah, Philip S. Yu, Bryan Hooi:
Sketch-Based Anomaly Detection in Streaming Graphs. KDD 2023: 93-104 - Jia-Qi Yang, Yucheng Xu, Jia-Lei Shen, Ke-Bin Fan, De-Chuan Zhan, Yang Yang:
IDToolkit: A Toolkit for Benchmarking and Developing Inverse Design Algorithms in Nanophotonics. KDD 2023: 2930-2940 - Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik:
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD 2023: 5870-5871 - Song Jiang, Zijie Huang, Xiao Luo, Yizhou Sun:
CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems. KDD 2023: 997-1009 - Mohamed Ragab, Emadeldeen Eldele, Min Wu, Chuan-Sheng Foo, Xiaoli Li, Zhenghua Chen:
Source-Free Domain Adaptation with Temporal Imputation for Time Series Data. KDD 2023: 1989-1998 - Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Learning for Counterfactual Fairness from Observational Data. KDD 2023: 1620-1630