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2020 – today
- 2024
[j49]Bolin Ding, Rong Zhu, Jingren Zhou:
Learned Query Optimizers. Found. Trends Databases 13(4): 250-310 (2024)- [j48]Jiajun Li
, Runlin Lei, Sibo Wang, Zhewei Wei, Bolin Ding:
Learning-based Property Estimation with Polynomials. Proc. ACM Manag. Data 2(3): 148 (2024) - [j47]Lianggui Weng, Rong Zhu, Di Wu, Bolin Ding, Bolong Zheng, Jingren Zhou:
Eraser: Eliminating Performance Regression on Learned Query Optimizer. Proc. VLDB Endow. 17(5): 926-938 (2024) - [j46]Rong Zhu, Lianggui Weng, Wenqing Wei, Di Wu, Jiazhen Peng, Yifan Wang, Bolin Ding, Defu Lian, Bolong Zheng, Jingren Zhou:
PilotScope: Steering Databases with Machine Learning Drivers. Proc. VLDB Endow. 17(5): 980-993 (2024) - [j45]Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, Jingren Zhou:
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation. Proc. VLDB Endow. 17(5): 1132-1145 (2024) - [j44]Zitao Li, Bolin Ding, Liuyi Yao, Yaliang Li, Xiaokui Xiao, Jingren Zhou:
Performance-Based Pricing of Federated Learning via Auction. Proc. VLDB Endow. 17(6): 1269-1282 (2024) - [j43]Fei Wei, Ergute Bao, Xiaokui Xiao, Yin Yang, Bolin Ding:
AAA: an Adaptive Mechanism for Locally Differential Private Mean Estimation. Proc. VLDB Endow. 17(8): 1843-1855 (2024) - [j42]Weirui Kuang, Zhen Wang, Zhewei Wei, Yaliang Li, Bolin Ding:
When Transformer Meets Large Graphs: An Expressive and Efficient Two-View Architecture. IEEE Trans. Knowl. Data Eng. 36(10): 5440-5452 (2024) - [j41]Xingguang Chen, Rong Zhu, Bolin Ding, Sibo Wang, Jingren Zhou:
Lero: applying learning-to-rank in query optimizer. VLDB J. 33(5): 1307-1331 (2024) - [c109]Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding:
When to Trust LLMs: Aligning Confidence with Response Quality. ACL (Findings) 2024: 5984-5996 - [c108]Yin Lin, Bolin Ding, H. V. Jagadish, Jingren Zhou:
SMARTFEAT: Efficient Feature Construction through Feature-Level Foundation Model Interactions. CIDR 2024 - [c107]Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study. LREC/COLING 2024: 5174-5190 - [c106]Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding:
Improving LoRA in Privacy-preserving Federated Learning. ICLR 2024 - [c105]Xue Wang, Tian Zhou, Qingsong Wen, Jinyang Gao, Bolin Ding, Rong Jin:
CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting. ICLR 2024 - [c104]Yanxi Chen, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou:
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism. ICML 2024 - [c103]Kexin Huang, Ziqian Chen, Xue Wang, Chongming Gao, Jinyang Gao, Bolin Ding, Xiang Wang:
Auctionformer: A Unified Deep Learning Algorithm for Solving Equilibrium Strategies in Auction Games. ICML 2024 - [c102]Zhen Qin, Daoyuan Chen, Bingchen Qian, Bolin Ding, Yaliang Li, Shuiguang Deng:
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes. ICML 2024 - [c101]Feijie Wu, Zitao Li, Yaliang Li, Bolin Ding, Jing Gao:
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model. KDD 2024: 3345-3355 - [c100]Fangyuan Zhao, Zitao Li, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li:
VertiMRF: Differentially Private Vertical Federated Data Synthesis. KDD 2024: 4431-4442 - [c99]Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning. KDD 2024: 5260-5271 - [c98]Daoyuan Chen, Yaliang Li, Bolin Ding:
Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases. KDD 2024: 6414-6415 - [c97]Yichen Qian, Yongyi He, Rong Zhu, Jintao Huang, Zhijian Ma, Haibin Wang, Yaohua Wang, Xiuyu Sun, Defu Lian, Bolin Ding, Jingren Zhou:
UniDM: A Unified Framework for Data Manipulation with Large Language Models. MLSys 2024 - [c96]Ke Zhang, Lichao Sun, Bolin Ding, Siu Ming Yiu, Carl Yang:
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning. SDM 2024: 806-814 - [c95]Daoyuan Chen, Yilun Huang, Zhijian Ma, Hesen Chen, Xuchen Pan, Ce Ge, Dawei Gao, Yuexiang Xie, Zhaoyang Liu, Jinyang Gao, Yaliang Li, Bolin Ding, Jingren Zhou:
Data-Juicer: A One-Stop Data Processing System for Large Language Models. SIGMOD Conference Companion 2024: 120-134 - [c94]Rong Zhu, Lianggui Weng, Bolin Ding, Jingren Zhou:
Learned Query Optimizer: What is New and What is Next. SIGMOD Conference Companion 2024: 561-569 - [c93]Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David A. Forsyth, Bo Li, Dawn Song:
SoK: Privacy-Preserving Data Synthesis. SP 2024: 4696-4713 - [c92]Zhen Wang, Yaliang Li, Bolin Ding, Yule Li, Zhewei Wei:
Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs. WWW 2024: 780-791 - [i85]Ke Zhang, Lichao Sun, Bolin Ding, Siu Ming Yiu, Carl Yang:
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning. CoRR abs/2401.04336 (2024) - [i84]Xuchen Pan, Yanxi Chen, Yaliang Li, Bolin Ding, Jingren Zhou:
EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models. CoRR abs/2402.00518 (2024) - [i83]Yue Cui, Liuyi Yao, Yaliang Li, Ziqian Chen, Bolin Ding, Xiaofang Zhou:
An Auction-based Marketplace for Model Trading in Federated Learning. CoRR abs/2402.01802 (2024) - [i82]Yuan Gao, Haokun Chen, Xiang Wang, Zhicai Wang, Xue Wang, Jinyang Gao, Bolin Ding:
DiffsFormer: A Diffusion Transformer on Stock Factor Augmentation. CoRR abs/2402.06656 (2024) - [i81]Dawei Gao, Zitao Li, Weirui Kuang, Xuchen Pan, Daoyuan Chen, Zhijian Ma, Bingchen Qian, Liuyi Yao, Lin Zhu, Chen Cheng, Hongzhu Shi, Yaliang Li, Bolin Ding, Jingren Zhou:
AgentScope: A Flexible yet Robust Multi-Agent Platform. CoRR abs/2402.14034 (2024) - [i80]Yue Cui, Liuyi Yao, Zitao Li, Yaliang Li, Bolin Ding, Xiaofang Zhou:
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning. CoRR abs/2402.15247 (2024) - [i79]Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding:
Improving LoRA in Privacy-preserving Federated Learning. CoRR abs/2403.12313 (2024) - [i78]Fei Wei, Ergute Bao, Xiaokui Xiao, Yin Yang, Bolin Ding:
AAA: an Adaptive Mechanism for Locally Differential Private Mean Estimation. CoRR abs/2404.01625 (2024) - [i77]Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding:
When to Trust LLMs: Aligning Confidence with Response Quality. CoRR abs/2404.17287 (2024) - [i76]Yichen Qian, Yongyi He, Rong Zhu, Jintao Huang, Zhijian Ma, Haibin Wang, Yaohua Wang, Xiuyu Sun, Defu Lian, Bolin Ding, Jingren Zhou:
UniDM: A Unified Framework for Data Manipulation with Large Language Models. CoRR abs/2405.06510 (2024) - [i75]Ce Ge, Zhijian Ma, Daoyuan Chen, Yaliang Li, Bolin Ding:
Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining. CoRR abs/2405.14908 (2024) - [i74]Tianjing Zeng, Junwei Lan, Jiahong Ma, Wenqing Wei, Rong Zhu, Pengfei Li, Bolin Ding, Defu Lian, Zhewei Wei, Jingren Zhou:
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation. CoRR abs/2406.01027 (2024) - [i73]Feijie Wu, Zitao Li, Yaliang Li, Bolin Ding, Jing Gao:
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model. CoRR abs/2406.17706 (2024) - [i72]Fangyuan Zhao, Zitao Li, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li:
VertiMRF: Differentially Private Vertical Federated Data Synthesis. CoRR abs/2406.19008 (2024) - [i71]Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization. CoRR abs/2407.07880 (2024) - [i70]Zhen Qin, Daoyuan Chen, Wenhao Zhang, Liuyi Yao, Yilun Huang, Bolin Ding, Yaliang Li, Shuiguang Deng:
The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective. CoRR abs/2407.08583 (2024) - [i69]Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
β-DPO: Direct Preference Optimization with Dynamic β. CoRR abs/2407.08639 (2024) - [i68]Daoyuan Chen, Haibin Wang, Yilun Huang, Ce Ge, Yaliang Li, Bolin Ding, Jingren Zhou:
Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development. CoRR abs/2407.11784 (2024) - [i67]Yanxi Chen, Yaliang Li, Bolin Ding, Jingren Zhou:
On the Design and Analysis of LLM-Based Algorithms. CoRR abs/2407.14788 (2024) - [i66]Xuchen Pan, Dawei Gao, Yuexiang Xie, Zhewei Wei, Yaliang Li, Bolin Ding, Ji-Rong Wen, Jingren Zhou:
Very Large-Scale Multi-Agent Simulation in AgentScope. CoRR abs/2407.17789 (2024) - [i65]Fangyuan Zhao, Yuexiang Xie, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li:
Understanding Byzantine Robustness in Federated Learning with A Black-box Server. CoRR abs/2408.06042 (2024) - [i64]Yuchang Sun, Yuexiang Xie, Bolin Ding, Yaliang Li, Jun Zhang:
Exploring Selective Layer Fine-Tuning in Federated Learning. CoRR abs/2408.15600 (2024) - 2023
- [j40]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) - [j39]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) - [j38]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) - [j37]Pengfei Li, Hua Lu, Rong Zhu, Bolin Ding, Long Yang, Gang Pan:
DILI: A Distribution-Driven Learned Index. Proc. VLDB Endow. 16(9): 2212-2224 (2023) - [j36]Dawei Gao, Daoyuan Chen, Zitao Li, Yuexiang Xie, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou:
FS-Real: A Real-World Cross-Device Federated Learning Platform. Proc. VLDB Endow. 16(12): 4046-4049 (2023) - [j35]Pengfei Li, Wenqing Wei, Rong Zhu, Bolin Ding, Jingren Zhou, Hua Lu:
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads. Proc. VLDB Endow. 17(2): 197-210 (2023) - [j34]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) - [j33]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) - [j32]Yang Deng, Yaliang Li, Bolin Ding, Wai Lam:
Leveraging Long Short-Term User Preference in Conversational Recommendation via Multi-agent Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(11): 11541-11555 (2023) - [j31]Ziqian Chen, Fei Sun, Yifan Tang, Haokun Chen, Jinyang Gao, Bolin Ding:
Studying the Impact of Data Disclosure Mechanism in Recommender Systems via Simulation. ACM Trans. Inf. Syst. 41(3): 60:1-60:26 (2023) - [c91]Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li:
Tunable Soft Prompts are Messengers in Federated Learning. EMNLP (Findings) 2023: 14665-14675 - [c90]Cong Zhang, Weiran Liu, Bolin Ding, Dongdai Lin:
Efficient Private Multiset ID Protocols. ICICS 2023: 351-369 - [c89]Daoyuan Chen, Wuchao Li, Yaliang Li, Bolin Ding, Kai Zeng, Defu Lian, Jingren Zhou:
Learned Index with Dynamic $\epsilon$. ICLR 2023 - [c88]Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li:
Efficient Personalized Federated Learning via Sparse Model-Adaptation. ICML 2023: 5234-5256 - [c87]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization. ICML 2023: 35908-35948 - [c86]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. KDD 2023: 3829-3841 - [c85]Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng:
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. KDD 2023: 4743-4755 - [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 - [i63]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) - [i62]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) - [i61]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) - [i60]Pengfei Li, Hua Lu, Rong Zhu, Bolin Ding, Long Yang, Gang Pan:
DILI: A Distribution-Driven Learned Index. CoRR abs/2304.08817 (2023) - [i59]Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li:
Efficient Personalized Federated Learning via Sparse Model-Adaptation. CoRR abs/2305.02776 (2023) - [i58]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) - [i57]Yuzheng Hu, Fan Wu, Qinbin Li, Yunhui Long, Gonzalo Munilla Garrido, Chang Ge, Bolin Ding, David A. Forsyth, Bo Li, Dawn Song:
SoK: Privacy-Preserving Data Synthesis. CoRR abs/2307.02106 (2023) - [i56]Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study. CoRR abs/2307.08072 (2023) - [i55]Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, Jingren Zhou:
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation. CoRR abs/2308.15363 (2023) - [i54]Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning. CoRR abs/2309.00363 (2023) - [i53]Daoyuan Chen, Yilun Huang, Zhijian Ma, Hesen Chen, Xuchen Pan, Ce Ge, Dawei Gao, Yuexiang Xie, Zhaoyang Liu, Jinyang Gao, Yaliang Li, Bolin Ding, Jingren Zhou:
Data-Juicer: A One-Stop Data Processing System for Large Language Models. CoRR abs/2309.02033 (2023) - [i52]Yin Lin, Bolin Ding, H. V. Jagadish, Jingren Zhou:
SMARTFEAT: Efficient Feature Construction through Feature-Level Foundation Model Interactions. CoRR abs/2309.07856 (2023) - [i51]Pengfei Li, Wenqing Wei, Rong Zhu, Bolin Ding, Jingren Zhou, Hua Lu:
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads (Extended). CoRR abs/2310.05349 (2023) - [i50]Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li:
Tunable Soft Prompts are Messengers in Federated Learning. CoRR abs/2311.06805 (2023) - [i49]Yanxi Chen, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou:
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism. CoRR abs/2312.04916 (2023) - [i48]Zhen Qin, Daoyuan Chen, Bingchen Qian, Bolin Ding, Yaliang Li, Shuiguang Deng:
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes. CoRR abs/2312.06353 (2023) - [i47]Cong Zhang, Weiran Liu, Bolin Ding, Dongdai Lin:
Efficient Private Multiset ID Protocols. IACR Cryptol. ePrint Arch. 2023: 986 (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]