| 2021 | Multi-Armed Bandits and Reinforcement Learning: Advancing Decision Making in E-Commerce and Beyond. | Daniel R. Jiang, Haipeng Luo, Chu Wang, Yingfei Wang |
| 2021 | Pre-training on Large-Scale Heterogeneous Graph. | Xunqiang Jiang, Tianrui Jia, Yuan Fang, Chuan Shi, Zhe Lin, Hui Wang |
| 2021 | FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters. | Wenqi Jiang, Zhenhao He, Shuai Zhang, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso |
| 2021 | Bootstrapping for Batch Active Sampling. | Heinrich Jiang, Maya R. Gupta |
| 2021 | Topic-time heatmaps for human-in-the-loop topic detection and tracking. | Hang Jiang, Doug Beeferman |
| 2021 | Cross-Network Learning with Partially Aligned Graph Convolutional Networks. | Meng Jiang |
| 2021 | ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations. | Sheo Yon Jhin, Minju Jo, Taeyong Kong, Jinsung Jeon, Noseong Park |
| 2021 | Knowledge-Guided Efficient Representation Learning for Biomedical Domain. | Kishlay Jha, Guangxu Xun, Nan Du, Aidong Zhang |
| 2021 | Fast and Memory-Efficient Tucker Decomposition for Answering Diverse Time Range Queries. | Jun-Gi Jang, U Kang |
| 2021 | Real-time Event Detection for Emergency Response Tutorial. | Alejandro Jaimes, Joel R. Tetreault |
| 2021 | Uncertainty-Aware Reliable Text Classification. | Yibo Hu, Latifur Khan |
| 2021 | TrajNet: A Trajectory-Based Deep Learning Model for Traffic Prediction. | Bo Hui, Da Yan, Haiquan Chen, Wei-Shinn Ku |
| 2021 | MPCSL - A Modular Pipeline for Causal Structure Learning. | Johannes Huegle, Christopher Hagedorn, Michael Perscheid, Hasso Plattner |
| 2021 | Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach. | Junhao Hua, Ling Yan, Huan Xu, Cheng Yang |
| 2021 | HMRL: Hyper-Meta Learning for Sparse Reward Reinforcement Learning Problem. | Yun Hua, Xiangfeng Wang, Bo Jin, Wenhao Li, Junchi Yan, Xiaofeng He, Hongyuan Zha |
| 2021 | Scaling Up Graph Neural Networks Via Graph Coarsening. | Zengfeng Huang, Shengzhong Zhang, Chong Xi, Tang Liu, Min Zhou |
| 2021 | Sliding Spectrum Decomposition for Diversified Recommendation. | Yanhua Huang, Weikun Wang, Lei Zhang, Ruiwen Xu |
| 2021 | Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters. | Yuzhen Huang, Xiaohan Wei, Xing Wang, Jiyan Yang, Bor-Yiing Su, Shivam Bharuka, Dhruv Choudhary, Zewei Jiang, Hai Zheng, Jack Langman |
| 2021 | HGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps. | Jizhou Huang, Haifeng Wang, Yibo Sun, Miao Fan, Zhengjie Huang, Chunyuan Yuan, Yawen Li |
| 2021 | Deep Inclusion Relation-aware Network for User Response Prediction at Fliggy. | Zai Huang, Mingyuan Tao, Bufeng Zhang |
| 2021 | A Broader Picture of Random-walk Based Graph Embedding. | Zexi Huang, Arlei Silva, Ambuj K. Singh |
| 2021 | Representation Learning on Knowledge Graphs for Node Importance Estimation. | Han Huang, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv, Hui Xiong |
| 2021 | DisenQNet: Disentangled Representation Learning for Educational Questions. | Zhenya Huang, Xin Lin, Hao Wang, Qi Liu, Enhong Chen, Jianhui Ma, Yu Su, Wei Tong |
| 2021 | MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. | Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, Jie Tang |
| 2021 | WIT: Workshop on deriving Insights from user-generated Text. | Estevam Hruschka, Tom M. Mitchell, Marko Grobelnik, Behzad Golshan |