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2020 – today
- 2023
[j35]Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. Proc. VLDB Endow. 16(5): 1059-1072 (2023)- [j34]Rong Zhu, Wei Chen, Bolin Ding, Xingguang Chen, Andreas Pfadler, Ziniu Wu, Jingren Zhou:
Lero: A Learning-to-Rank Query Optimizer. Proc. VLDB Endow. 16(6): 1466-1479 (2023) - [j33]Xu Chen, Zhen Wang, Shuncheng Liu, Yaliang Li, Kai Zeng, Bolin Ding, Jingren Zhou, Han Su, Kai Zheng:
BASE: Bridging the Gap between Cost and Latency for Query Optimization. Proc. VLDB Endow. 16(8): 1958-1966 (2023) - [j32]Yexuan Shi
, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Bolin Ding, Lei Chen:
Efficient Approximate Range Aggregation Over Large-Scale Spatial Data Federation. IEEE Trans. Knowl. Data Eng. 35(1): 418-430 (2023) - [j31]Hengtong Zhang, Yaliang Li, Bolin Ding, Jing Gao:
LOKI: A Practical Data Poisoning Attack Framework Against Next Item Recommendations. IEEE Trans. Knowl. Data Eng. 35(5): 5047-5059 (2023) - [c84]Bolin Ding, Yiding Feng, Chien-Ju Ho, Wei Tang, Haifeng Xu:
Competitive Information Design for Pandora's Box. SODA 2023: 353-381 - [c83]Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou, Jinduo Liu, Mengdi Huai, Jing Gao:
Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning. WWW 2023: 3680-3688 - [i52]Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng:
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. CoRR abs/2302.01677 (2023) - [i51]Rong Zhu, Wei Chen, Bolin Ding, Xingguang Chen, Andreas Pfadler, Ziniu Wu, Jingren Zhou:
Lero: A Learning-to-Rank Query Optimizer. CoRR abs/2302.06873 (2023) - [i50]Daoyuan Chen, Dawei Gao, Yuexiang Xie, Xuchen Pan, Zitao Li, Yaliang Li, Bolin Ding, Jingren Zhou:
FS-Real: Towards Real-World Cross-Device Federated Learning. CoRR abs/2303.13363 (2023) - [i49]Pengfei Li, Hua Lu, Rong Zhu, Bolin Ding, Long Yang, Gang Pan:
DILI: A Distribution-Driven Learned Index. CoRR abs/2304.08817 (2023) - [i48]Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li:
Efficient Personalized Federated Learning via Sparse Model-Adaptation. CoRR abs/2305.02776 (2023) - [i47]Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin:
Make Transformer Great Again for Time Series Forecasting: Channel Aligned Robust Dual Transformer. CoRR abs/2305.12095 (2023) - 2022
- [j30]Siqing Li, Yaliang Li, Wayne Xin Zhao, Bolin Ding, Ji-Rong Wen:
Interpretable Aspect-Aware Capsule Network for Peer Review Based Citation Count Prediction. ACM Trans. Inf. Syst. 40(1): 11:1-11:29 (2022) - [j29]Yang Deng, Yaliang Li, Wenxuan Zhang, Bolin Ding, Wai Lam:
Toward Personalized Answer Generation in E-Commerce via Multi-perspective Preference Modeling. ACM Trans. Inf. Syst. 40(4): 87:1-87:28 (2022) - [c82]Shanlei Mu, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Bolin Ding:
ID-Agnostic User Behavior Pre-training for Sequential Recommendation. CCIR 2022: 16-27 - [c81]Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou:
Strengthening Order Preserving Encryption with Differential Privacy. CCS 2022: 2519-2533 - [c80]Jinjia Feng, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei, Hongteng Xu:
MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio. CIKM 2022: 509-519 - [c79]Rong Zhu, Ziniu Wu, Chengliang Chai, Andreas Pfadler, Bolin Ding, Guoliang Li, Jingren Zhou:
Learned Query Optimizer: At the Forefront of AI-Driven Databases. EDBT 2022: 1-4 - [c78]Xu Xie, Fei Sun, Zhaoyang Liu, Shiwen Wu, Jinyang Gao, Jiandong Zhang, Bolin Ding, Bin Cui:
Contrastive Learning for Sequential Recommendation. ICDE 2022: 1259-1273 - [c77]Yexuan Shi, Yongxin Tong, Yuxiang Zeng, Zimu Zhou, Bolin Ding, Lei Chen:
Efficient Approximate Range Aggregation over Large-scale Spatial Data Federation (Extended Abstract). ICDE 2022: 1559-1560 - [c76]Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding:
iFlood: A Stable and Effective Regularizer. ICLR 2022 - [c75]Dawei Gao, Yuexiang Xie, Zimu Zhou, Zhen Wang, Yaliang Li, Bolin Ding:
Finding Meta Winning Ticket to Train Your MAML. KDD 2022: 411-420 - [c74]Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Towards Universal Sequence Representation Learning for Recommender Systems. KDD 2022: 585-593 - [c73]Jiajun Li, Zhewei Wei, Bolin Ding, Xiening Dai, Lu Lu, Jingren Zhou:
Sampling-based Estimation of the Number of Distinct Values in Distributed Environment. KDD 2022: 893-903 - [c72]Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding:
Graph Neural Networks with Node-wise Architecture. KDD 2022: 1949-1958 - [c71]Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. KDD 2022: 4110-4120 - [c70]Yaliang Li, Bolin Ding, Jingren Zhou:
A Practical Introduction to Federated Learning. KDD 2022: 4802-4803 - [c69]Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding:
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning. NeurIPS 2022 - [c68]Jiawei Jiang, Lukas Burkhalter, Fangcheng Fu, Bolin Ding, Bo Du, Anwar Hithnawi, Bo Li, Ce Zhang:
VF-PS: How to Select Important Participants in Vertical Federated Learning, Efficiently and Securely? NeurIPS 2022 - [c67]Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei:
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. NeurIPS 2022 - [c66]Shanlei Mu, Yaliang Li, Wayne Xin Zhao, Jingyuan Wang, Bolin Ding, Ji-Rong Wen:
Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator. SIGIR 2022: 1401-1411 - [c65]Jinglin Peng, Bolin Ding, Jiannan Wang, Kai Zeng, Jingren Zhou:
One Size Does Not Fit All: A Bandit-Based Sampler Combination Framework with Theoretical Guarantees. SIGMOD Conference 2022: 531-544 - [c64]Yiqing Xie, Zhen Wang, Carl Yang, Yaliang Li, Bolin Ding, Hongbo Deng, Jiawei Han:
KoMen: Domain Knowledge Guided Interaction Recommendation for Emerging Scenarios. WWW 2022: 1301-1310 - [c63]Chong Chen, Fei Sun, Min Zhang, Bolin Ding:
Recommendation Unlearning. WWW 2022: 2768-2777 - [c62]Shaoyun Shi, Yuexiang Xie, Zhen Wang, Bolin Ding, Yaliang Li, Min Zhang:
Explainable Neural Rule Learning. WWW 2022: 3031-3041 - [i46]Chong Chen, Fei Sun, Min Zhang, Bolin Ding:
Recommendation Unlearning. CoRR abs/2201.06820 (2022) - [i45]Renzhi Wu, Bolin Ding, Xu Chu, Zhewei Wei, Xiening Dai, Tao Guan, Jingren Zhou:
Learning to be a Statistician: Learned Estimator for Number of Distinct Values. CoRR abs/2202.02800 (2022) - [i44]Ziqian Chen, Fei Sun, Yifan Tang, Haokun Chen, Jinyang Gao, Bolin Ding:
Proactively Control Privacy in Recommender Systems. CoRR abs/2204.00279 (2022) - [i43]Yuexiang Xie, Zhen Wang, Daoyuan Chen, Dawei Gao, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing. CoRR abs/2204.05011 (2022) - [i42]Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. CoRR abs/2204.05562 (2022) - [i41]Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei:
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. CoRR abs/2205.13892 (2022) - [i40]Shanlei Mu, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Bolin Ding:
ID-Agnostic User Behavior Pre-training for Sequential Recommendation. CoRR abs/2206.02323 (2022) - [i39]Liuyi Yao, Dawei Gao, Zhen Wang, Yuexiang Xie, Weirui Kuang, Daoyuan Chen, Haohui Wang, Chenhe Dong, Bolin Ding, Yaliang Li:
A Benchmark for Federated Hetero-Task Learning. CoRR abs/2206.03436 (2022) - [i38]Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding:
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning. CoRR abs/2206.03655 (2022) - [i37]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization. CoRR abs/2206.03966 (2022) - [i36]Jiajun Li, Zhewei Wei, Bolin Ding, Xiening Dai, Lu Lu, Jingren Zhou:
Sampling-based Estimation of the Number of Distinct Values in Distributed Environment. CoRR abs/2206.05476 (2022) - [i35]Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Towards Universal Sequence Representation Learning for Recommender Systems. CoRR abs/2206.05941 (2022) - [i34]Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li:
Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning. CoRR abs/2212.05789 (2022) - 2021
- [j28]Ergute Bao, Xiaokui Xiao, Jun Zhao, Dongping Zhang, Bolin Ding:
Synthetic Data Generation with Differential Privacy via Bayesian Networks. J. Priv. Confidentiality 11(3) (2021) - [j27]Shuyuan Yan, Bolin Ding, Wei Guo, Jingren Zhou, Zhewei Wei, Xiaowei Jiang, Sheng Xu:
FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data. Proc. VLDB Endow. 14(5): 721-729 (2021) - [j26]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. Proc. VLDB Endow. 14(11): 2167-2176 (2021) - [j25]Ergute Bao, Yin Yang, Xiaokui Xiao, Bolin Ding:
CGM: An Enhanced Mechanism for Streaming Data Collectionwith Local Differential Privacy. Proc. VLDB Endow. 14(11): 2258-2270 (2021) - [j24]Jiaxiang Liu, Karl Knopf, Yiqing Tan, Bolin Ding, Xi He:
Catch a Blowfish Alive: A Demonstration of Policy-Aware Differential Privacy for Interactive Data Exploration. Proc. VLDB Endow. 14(12): 2859-2862 (2021) - [j23]Renzhi Wu, Bolin Ding, Xu Chu, Zhewei Wei, Xiening Dai, Tao Guan, Jingren Zhou:
Learning to be a Statistician: Learned Estimator for Number of Distinct Values. Proc. VLDB Endow. 15(2): 272-284 (2021) - [j22]Zitao Li, Bolin Ding, Ce Zhang, Ninghui Li, Jingren Zhou:
Federated Matrix Factorization with Privacy Guarantee. Proc. VLDB Endow. 15(4): 900-913 (2021) - [j21]Yongxin Tong, Yuxiang Zeng, Bolin Ding, Libin Wang, Lei Chen:
Two-Sided Online Micro-Task Assignment in Spatial Crowdsourcing. IEEE Trans. Knowl. Data Eng. 33(5): 2295-2309 (2021) - [c61]Xu Xie, Zhaoyang Liu, Shiwen Wu, Fei Sun, Cihang Liu, Jiawei Chen, Jinyang Gao, Bin Cui, Bolin Ding:
CausCF: Causal Collaborative Filtering for Recommendation Effect Estimation. CIKM 2021: 4253-4263 - [c60]Yaliang Li, Zhen Wang, Yuexiang Xie, Bolin Ding, Kai Zeng, Ce Zhang:
AutoML: From Methodology to Application. CIKM 2021: 4853-4856 - [c59]Yuexiang Xie, Fei Sun, Yang Deng, Yaliang Li, Bolin Ding:
Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation. EMNLP (Findings) 2021: 100-110 - [c58]Siqing Li, Liuyi Yao, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Tonglei Guo, Bolin Ding, Ji-Rong Wen:
Debiasing Learning based Cross-domain Recommendation. KDD 2021: 3190-3199 - [c57]Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou:
FIVES: Feature Interaction Via Edge Search for Large-Scale Tabular Data. KDD 2021: 3795-3805 - [c56]Yaliang Li, Zhen Wang, Bolin Ding, Ce Zhang:
AutoML: A Perspective where Industry Meets Academy. KDD 2021: 4048-4049 - [c55]Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, Wai Lam:
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning. SIGIR 2021: 1431-1441 - [c54]Mingyu Xiao, Sen Huang, Yi Zhou, Bolin Ding:
Efficient Reductions and a Fast Algorithm of Maximum Weighted Independent Set. WWW 2021: 3930-3940 - [i33]Yaliang Li, Daoyuan Chen, Bolin Ding, Kai Zeng, Jingren Zhou:
A Pluggable Learned Index Method via Sampling and Gap Insertion. CoRR abs/2101.00808 (2021) - [i32]Shuyuan Yan, Bolin Ding, Wei Guo, Jingren Zhou, Zhewei Wei, Xiaowei Jiang, Sheng Xu:
FlashP: An Analytical Pipeline for Real-time Forecasting of Time-Series Relational Data. CoRR abs/2101.03298 (2021) - [i31]Bolin Ding, Yiding Feng, Chien-Ju Ho, Wei Tang:
Competitive Information Disclosure with Multiple Receivers. CoRR abs/2103.03769 (2021) - [i30]Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, Wai Lam:
Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning. CoRR abs/2105.09710 (2021) - [i29]Xu Xie, Zhaoyang Liu, Shiwen Wu, Fei Sun, Cihang Liu, Jiawei Chen, Jinyang Gao, Bin Cui, Bolin Ding:
CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation. CoRR abs/2105.13881 (2021) - [i28]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. CoRR abs/2107.08861 (2021) - [i27]Yuexiang Xie, Fei Sun, Yang Deng, Yaliang Li, Bolin Ding:
Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation. CoRR abs/2108.13134 (2021) - [i26]Rong Zhu, Tianjing Zeng, Andreas Pfadler, Wei Chen, Bolin Ding, Jingren Zhou:
Glue: Adaptively Merging Single Table Cardinality to Estimate Join Query Size. CoRR abs/2112.03458 (2021) - [i25]Yang Deng, Yaliang Li, Wenxuan Zhang, Bolin Ding, Wai Lam:
Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling. CoRR abs/2112.13556 (2021) - [i24]Andreas Pfadler, Rong Zhu, Wei Chen, Botong Huang, Tianjing Zeng, Bolin Ding, Jingren Zhou:
Baihe: SysML Framework for AI-driven Databases. CoRR abs/2112.14460 (2021) - 2020
- [j20]Jie Tang, Shaoshan Liu, Jie Cao, Dawei Sun, Bolin Ding, Jean-Luc Gaudiot, Weisong Shi:
π-Hub: Large-scale video learning, storage, and retrieval on heterogeneous hardware platforms. Future Gener. Comput. Syst. 102: 514-523 (2020) - [j19]Min Xu, Bolin Ding, Tianhao Wang, Jingren Zhou:
Collecting and Analyzing Data Jointly from Multiple Services under Local Differential Privacy. Proc. VLDB Endow. 13(11): 2760-2772 (2020) - [j18]Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha:
Improving Utility and Security of the Shuffler-based Differential Privacy. Proc. VLDB Endow. 13(13): 3545-3558 (2020) - [c53]Daoyuan Chen, Yaliang Li, Bolin Ding, Ying Shen:
An Adaptive Embedding Framework for Heterogeneous Information Networks. CIKM 2020: 165-174 - [c52]Yaliang Li, Houping Xiao, Zhan Qin, Chenglin Miao, Lu Su, Jing Gao, Kui Ren, Bolin Ding:
Towards Differentially Private Truth Discovery for Crowd Sensing Systems. ICDCS 2020: 1156-1166 - [c51]Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li:
Automated Relational Meta-learning. ICLR 2020 - [c50]Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, Yaliang Li:
Simple and Deep Graph Convolutional Networks. ICML 2020: 1725-1735 - [c49]Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou:
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search. IJCAI 2020: 2463-2469 - [c48]Zhaoyang Liu, Haokun Chen, Fei Sun, Xu Xie, Jinyang Gao, Bolin Ding, Yanyan Shen:
Intent Preference Decoupling for User Representation on Online Recommender System. IJCAI 2020: 2575-2582 - [c47]Zhuolun Xiang, Bolin Ding, Xi He, Jingren Zhou:
Linear and Range Counting under Metric-based Local Differential Privacy. ISIT 2020: 908-913 - [c46]Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, Ji-Rong Wen:
Scalable Graph Neural Networks via Bidirectional Propagation. NeurIPS 2020 - [c45]Zhiqiang Tao, Yaliang Li, Bolin Ding, Ce Zhang, Jingren Zhou, Yun Fu:
Learning to Mutate with Hypergradient Guided Population. NeurIPS 2020 - [c44]Ruiyang Ren, Zhaoyang Liu, Yaliang Li, Wayne Xin Zhao, Hui Wang, Bolin Ding, Ji-Rong Wen:
Sequential Recommendation with Self-Attentive Multi-Adversarial Network. SIGIR 2020: 89-98 - [c43]Hengtong Zhang, Yaliang Li, Bolin Ding, Jing Gao:
Practical Data Poisoning Attack against Next-Item Recommendation. WWW 2020: 2458-2464 - [i23]Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li:
Automated Relational Meta-learning. CoRR abs/2001.00745 (2020) - [i22]Daoyuan Chen, Yaliang Li, Minghui Qiu, Zhen Wang, Bofang Li, Bolin Ding, Hongbo Deng, Jun Huang, Wei Lin, Jingren Zhou:
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search. CoRR abs/2001.04246 (2020) - [i21]Hengtong Zhang, Yaliang Li, Bolin Ding, Jing Gao:
Practical Data Poisoning Attack against Next-Item Recommendation. CoRR abs/2004.03728 (2020) - [i20]Ruiyang Ren, Zhaoyang Liu, Yaliang Li, Wayne Xin Zhao, Hui Wang, Bolin Ding, Ji-Rong Wen:
Sequential Recommendation with Self-Attentive Multi-Adversarial Network. CoRR abs/2005.10602 (2020) - [i19]Ming Chen, Zhewei Wei, Zengfeng Huang, Bolin Ding, Yaliang Li:
Simple and Deep Graph Convolutional Networks. CoRR abs/2007.02133 (2020) - [i18]Yuexiang Xie, Zhen Wang, Yaliang Li, Bolin Ding, Nezihe Merve Gürel, Ce Zhang, Minlie Huang, Wei Lin, Jingren Zhou:
Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph. CoRR abs/2007.14573 (2020) - [i17]Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou:
Intertwining Order Preserving Encryption and Differential Privacy. CoRR abs/2009.05679 (2020) - [i16]Xu Xie, Fei Sun, Zhaoyang Liu, Jinyang Gao, Bolin Ding, Bin Cui:
Contrastive Pre-training for Sequential Recommendation. CoRR abs/2010.14395 (2020) - [i15]Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, Ji-Rong Wen:
Scalable Graph Neural Networks via Bidirectional Propagation. CoRR abs/2010.15421 (2020)
2010 – 2019
- 2019
- [j17]Min Xu, Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang:
DPSAaS: Multi-Dimensional Data Sharing and Analytics as Services under Local Differential Privacy. Proc. VLDB Endow. 12(12): 1862-1865 (2019) - [c42]Silu Huang, Chi Wang, Bolin Ding, Surajit Chaudhuri:
Efficient Identification of Approximate Best Configuration of Training in Large Datasets. AAAI 2019: 3862-3869 - [c41]Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang:
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. MLSys 2019 - [c40]Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin:
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors. NeurIPS 2019: 13635-13646 - [c39]Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha:
Answering Multi-Dimensional Analytical Queries under Local Differential Privacy. SIGMOD Conference 2019: 159-176 - [i14]Cédric Renggli, Bojan Karlas, Bolin Ding, Feng Liu, Kevin Schawinski, Wentao Wu, Ce Zhang:
Continuous Integration of Machine Learning Models with ease.ml/ci: Towards a Rigorous Yet Practical Treatment. CoRR abs/1903.00278 (2019) - [i13]Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Ninghui Li, Somesh Jha:
Practical and Robust Privacy Amplification with Multi-Party Differential Privacy. CoRR abs/1908.11515 (2019) - [i12]Zhuolun Xiang, Bolin Ding, Xi He, Jingren Zhou:
Design of Algorithms under Policy-Aware Local Differential Privacy: Utility-Privacy Trade-offs. CoRR abs/1909.11778 (2019) - 2018
- [j16]Azade Nazi, Bolin Ding, Vivek R. Narasayya, Surajit Chaudhuri:
Efficient Estimation of Inclusion Coefficient using HyperLogLog Sketches. Proc. VLDB Endow. 11(10): 1097-1109 (2018) - [c38]Bolin Ding, Harsha Nori, Paul Li, Joshua Allen:
Comparing Population Means Under Local Differential Privacy: With Significance and Power. AAAI 2018: 26-33 - [c37]Yaliang Li, Chenglin Miao, Lu Su, Jing Gao, Qi Li, Bolin Ding, Zhan Qin, Kui Ren:
An Efficient Two-Layer Mechanism for Privacy-Preserving Truth Discovery. KDD 2018: 1705-1714 - [c36]Adam Dziedzic, Jingjing Wang, Sudipto Das, Bolin Ding, Vivek R. Narasayya, Manoj Syamala:
Columnstore and B+ tree - Are Hybrid Physical Designs Important? SIGMOD Conference 2018: 177-190 - [r2]Jiawei Han, Bolin Ding:
Stream Mining. Encyclopedia of Database Systems (2nd ed.) 2018 - [i11]Bolin Ding, Harsha Nori, Paul Li, Joshua Allen:
Comparing Population Means under Local Differential Privacy: with Significance and Power. CoRR abs/1803.09027 (2018) - [i10]Joshua Allen, Bolin Ding, Janardhan Kulkarni, Harsha Nori, Olga Ohrimenko, Sergey Yekhanin:
An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors. CoRR abs/1807.00736 (2018) - [i9]