Understanding information seeking in digital libraries: antecedents and consequences. - Xianjin Zha; Wentao Wang; Yalan Yan; Jinchao Zhang; Daochen Zha (Aslib J. Inf. Manag., 2015)

Sound information seeking in Web 2.0 virtual communities: the moderating effect of mindfulness. - Xianjin Zha; Jinchao Zhang; Yalan Yan; Daochen Zha (Behav. Inf. Technol., 2015)

A Security-Enhanced vTPM 2.0 for Cloud Computing. - Juan Wang 006; Feng Xiao; Jianwei Huang; Daochen Zha; Chengyang Fan; Wei Hu; Huanguo Zhang (ICICS, 2017)

CHAOS: an SDN-based Moving Target Defense System. - Juan Wang 006; Feng Xiao; Jianwei Huang; Daochen Zha; Hongxin Hu; Huanguo Zhang (CoRR, 2017)

CHAOS: An SDN-Based Moving Target Defense System. - Yuan Shi; Huanguo Zhang; Juan Wang 006; Feng Xiao; Jianwei Huang; Daochen Zha; Hongxin Hu; Fei Yan 008; Bo Zhao 023 (Secur. Commun. Networks, 2017)

Experience Replay Optimization. - Daochen Zha; Kwei-Herng Lai; Kaixiong Zhou; Xia Hu 001 (IJCAI, 2019)

PyODDS: An End-to-End Outlier Detection System. - Yuening Li; Daochen Zha; Na Zou 001; Xia Hu 001 (CoRR, 2019)

RLCard: A Toolkit for Reinforcement Learning in Card Games. - Daochen Zha; Kwei-Herng Lai; Yuanpu Cao; Songyi Huang; Ruzhe Wei; Junyu Guo; Xia Hu 001 (CoRR, 2019)

Multi-Channel Graph Convolutional Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Daochen Zha; Na Zou 001; Xia Hu 001 (CoRR, 2019)

Multi-label dataless text classification with topic modeling. - Daochen Zha; Chenliang Li (Knowl. Inf. Syst., 2019)

Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning. - Daochen Zha; Kwei-Herng Lai; Mingyang Wan; Xia Hu 001 (ICDM, 2020)

Dual Policy Distillation. - Kwei-Herng Lai; Daochen Zha; Yuening Li; Xia Hu 001 (IJCAI, 2020)

RLCard: A Platform for Reinforcement Learning in Card Games. - Daochen Zha; Kwei-Herng Lai; Songyi Huang; Yuanpu Cao; Keerthana Reddy; Juan Vargas; Alex Nguyen 004; Ruzhe Wei; Junyu Guo; Xia Hu 001 (IJCAI, 2020)

Multi-Channel Graph Neural Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Daochen Zha; Na Zou 001; Xia Hu 001 (IJCAI, 2020)

Policy-GNN: Aggregation Optimization for Graph Neural Networks. - Kwei-Herng Lai; Daochen Zha; Kaixiong Zhou; Xia Hu 001 (KDD, 2020)

Towards Deeper Graph Neural Networks with Differentiable Group Normalization. - Kaixiong Zhou; Xiao Huang 001; Yuening Li; Daochen Zha; Rui Chen 012; Xia Hu 001 (NeurIPS, 2020)

PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning. - Yuening Li; Daochen Zha; Praveen Kumar Venugopal; Na Zou 001; Xia Hu 001 (WWW (Companion Volume), 2020)

AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning. - Yuening Li; Zhengzhang Chen; Daochen Zha; Kaixiong Zhou; Haifeng Jin; Haifeng Chen; Xia Hu 001 (CoRR, 2020)

TODS: An Automated Time Series Outlier Detection System. - Kwei-Herng Lai; Daochen Zha; Guanchu Wang; Junjie Xu; Yue Zhao 016; Devesh Kumar; Yile Chen 002; Purav Zumkhawaka; Minyang Wan; Diego Martinez; Xia Ben Hu (AAAI, 2021)

AutoOD: Neural Architecture Search for Outlier Detection. - Yuening Li; Zhengzhang Chen; Daochen Zha; Kaixiong Zhou; Haifeng Jin; Haifeng Chen; Xia Hu 001 (ICDE, 2021)

Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments. - Daochen Zha; Wenye Ma; Lei Yuan; Xia Hu 001; Ji Liu (ICLR, 2021)

DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning. - Daochen Zha; Jingru Xie; Wenye Ma; Sheng Zhang; Xiangru Lian; Xia Hu 001; Ji Liu (ICML, 2021)

Revisiting Time Series Outlier Detection: Definitions and Benchmarks. - Kwei-Herng Lai; Daochen Zha; Junjie Xu; Yue Zhao 016; Guanchu Wang; Xia Ben Hu (NeurIPS Datasets and Benchmarks, 2021)

Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. - Kaixiong Zhou; Xiao Huang 001; Daochen Zha; Rui Chen 012; Li Li 035; Soo-Hyun Choi; Xia Hu 001 (NeurIPS, 2021)

Learning Disentangled Representations for Time Series. - Yuening Li; Zhengzhang Chen; Daochen Zha; Mengnan Du; Denghui Zhang; Haifeng Chen; Xia Hu 001 (CoRR, 2021)

Simplifying Deep Reinforcement Learning via Self-Supervision. - Daochen Zha; Kwei-Herng Lai; Kaixiong Zhou; Xia Hu 001 (CoRR, 2021)

AutoVideo: An Automated Video Action Recognition System. - Daochen Zha; Zaid Pervaiz Bhat; Yi-Wei Chen; Yicheng Wang; Sirui Ding; Anmoll Kumar Jain; Mohammad Qazim Bhat; Kwei-Herng Lai; Jiaben Chen; Na Zou 001; Xia Hu 001 (CoRR, 2021)

Modeling Techniques for Machine Learning Fairness: A Survey. - Mingyang Wan; Daochen Zha; Ninghao Liu; Na Zou 001 (CoRR, 2021)

Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. - Sirui Ding; Ruixiang Tang; Daochen Zha; Na Zou 001; Kai Zhang 041; Xiaoqian Jiang; Xia Hu 001 (AMIA, 2022)

BED: A Real-Time Object Detection System for Edge Devices. - Guanchu Wang; Zaid Pervaiz Bhat; Zhimeng Jiang; Yi-Wei Chen; Daochen Zha; Alfredo Costilla-Reyes; Afshin Niktash; Mehmet Görkem Ulkar; Osman Erman Okman; Xuanting Cai; Xia Ben Hu (CIKM, 2022)

Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning. - Daochen Zha; Kwei-Herng Lai; Qiaoyu Tan; Sirui Ding; Na Zou 001; Xia Ben Hu (CIKM, 2022)

AutoVideo: An Automated Video Action Recognition System. - Daochen Zha; Zaid Pervaiz Bhat; Yi-Wei Chen; Yicheng Wang; Sirui Ding; Jiaben Chen; Kwei-Herng Lai; Mohammad Qazim Bhat; Anmoll Kumar Jain; Alfredo Costilla-Reyes; Na Zou 001; Xia Hu 001 (IJCAI, 2022)

Towards Learning Disentangled Representations for Time Series. - Yuening Li; Zhengzhang Chen; Daochen Zha; Mengnan Du; Jingchao Ni; Denghui Zhang; Haifeng Chen; Xia Hu 001 (KDD, 2022)

AutoShard: Automated Embedding Table Sharding for Recommender Systems. - Daochen Zha; Louis Feng; Bhargav Bhushanam; Dhruv Choudhary; Jade Nie; Yuandong Tian; Jay Chae; Yinbin Ma; Arun Kejariwal; Xia Hu 001 (KDD, 2022)

DreamShard: Generalizable Embedding Table Placement for Recommender Systems. - Daochen Zha; Louis Feng; Qiaoyu Tan; Zirui Liu 001; Kwei-Herng Lai; Bhargav Bhushanam; Yuandong Tian; Arun Kejariwal; Xia Hu 001 (NeurIPS, 2022)

Towards Similarity-Aware Time-Series Classification. - Daochen Zha; Kwei-Herng Lai; Kaixiong Zhou; Xia Hu 001 (SDM, 2022)

BED: A Real-Time Object Detection System for Edge Devices. - Guanchu Wang; Zaid Pervaiz Bhat; Zhimeng Jiang; Yi-Wei Chen; Daochen Zha; Alfredo Costilla-Reyes; Afshin Niktash; Mehmet Görkem Ulkar; Osman Erman Okman; Xia Ben Hu (CoRR, 2022)

Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture. - Yicheng Wang; Xiaotian Han; Chia-Yuan Chang 002; Daochen Zha; Ulisses Braga-Neto; Xia Hu 001 (CoRR, 2022)

RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations. - Zirui Liu 001; Shengyuan Chen; Kaixiong Zhou; Daochen Zha; Xiao Huang 001; Xia Hu 001 (CoRR, 2022)

Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning. - Yuening Li; Zhengzhang Chen; Daochen Zha; Kaixiong Zhou; Haifeng Jin; Haifeng Chen; Xia Hu 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. - Yu-Neng Chuang; Guanchu Wang; Chia-Yuan Chang 002; Kwei-Herng Lai; Daochen Zha; Ruixiang Tang; Fan Yang 023; Alfredo Costilla-Reyes; Kaixiong Zhou; Xiaoqian Jiang; Xia Hu 001 (CIKM, 2023)

Tackling Diverse Minorities in Imbalanced Classification. - Kwei-Herng Lai; Daochen Zha; Huiyuan Chen; Mangesh Bendre; Yuzhong Chen; Mahashweta Das; Hao Yang 007; Xia Hu 001 (CIKM, 2023)

Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation. - Qiaoyu Tan; Daochen Zha; Ninghao Liu; Soo-Hyun Choi; Li Li 035; Rui Chen 012; Xia Hu 001 (ICDM, 2023)

Mitigating Metastable Failures in Distributed Systems with Offline Reinforcement Learning. - Yueying Li; Daochen Zha; Tianjun Zhang; G. Edward Suh; Christina Delimitrou; Francis Y. Yan (Tiny Papers @ ICLR, 2023)

SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems. - Aaron M. Ferber; Taoan Huang; Daochen Zha; Martin Schubert; Benoit Steiner; Bistra Dilkina; Yuandong Tian (ICML, 2023)

RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations. - Zirui Liu 001; Shengyuan Chen; Kaixiong Zhou; Daochen Zha; Xiao Huang 001; Xia Hu 001 (ICML, 2023)

Data-centric AI: Techniques and Future Perspectives. - Daochen Zha; Kwei-Herng Lai; Fan Yang 023; Na Zou 001; Huiji Gao; Xia Hu 001 (KDD, 2023)

Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. - Daochen Zha; Louis Feng; Liang Luo; Bhargav Bhushanam; Zirui Liu 001; Yusuo Hu; Jade Nie; Yuzhen Huang; Yuandong Tian; Arun Kejariwal; Xia Hu 001 (MLSys, 2023)

Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. - Zirui Liu 001; Guanchu Wang; Shaochen Zhong; Zhaozhuo Xu; Daochen Zha; Ruixiang (Ryan) Tang; Zhimeng Stephen Jiang; Kaixiong Zhou; Vipin Chaudhary; Shuai Xu; Xia Hu 001 (NeurIPS, 2023)

One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning. - Shaochen (Henry) Zhong; Zaichuan You; Jiamu Zhang; Sebastian Zhao; Zachary LeClaire; Zirui Liu 001; Daochen Zha; Vipin Chaudhary; Shuai Xu; Xia Hu 001 (NeurIPS, 2023)

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning. - Zhiyao Zhou; Sheng Zhou 004; Bochao Mao; Xuanyi Zhou; Jiawei Chen 007; Qiaoyu Tan; Daochen Zha; Yan Feng; Chun Chen 001; Can Wang 001 (NeurIPS, 2023)

Data-centric AI: Perspectives and Challenges. - Daochen Zha; Zaid Pervaiz Bhat; Kwei-Herng Lai; Fan Yang 023; Xia Hu 001 (SDM, 2023)

Adaptive Popularity Debiasing Aggregator for Graph Collaborative Filtering. - Huachi Zhou; Hao Chen 062; Junnan Dong; Daochen Zha; Chuang Zhou 002; Xiao Huang 001 (SIGIR, 2023)

Enhanced Generalization Through Prioritization and Diversity in Self-Imitation Reinforcement Learning Over Procedural Environments with Sparse Rewards. - Alain Andres; Daochen Zha; Javier Del Ser (SSCI, 2023)

Active Ensemble Learning for Knowledge Graph Error Detection. - Junnan Dong; Qinggang Zhang; Xiao Huang 001; Qiaoyu Tan; Daochen Zha; Zihao Zhao (WSDM, 2023)

Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection. - Qiaoyu Tan; Xin Zhang 104; Ninghao Liu; Daochen Zha; Li Li 035; Rui Chen 012; Soo-Hyun Choi; Xia Hu 001 (WSDM, 2023)

Towards Personalized Preprocessing Pipeline Search. - Diego Martinez; Daochen Zha; Qiaoyu Tan; Xia Hu 001 (CoRR, 2023)

Interactive System-wise Anomaly Detection. - Guanchu Wang; Ninghao Liu; Daochen Zha; Xia Ben Hu (CoRR, 2023)

FinGPT: Democratizing Internet-scale Data for Financial Large Language Models. - Xiao-Yang Liu; Guoxuan Wang; Daochen Zha (CoRR, 2023)

KnowGPT: Black-Box Knowledge Injection for Large Language Models. - Qinggang Zhang; Junnan Dong; Hao Chen 062; Xiao Huang 001; Daochen Zha; Zailiang Yu (CoRR, 2023)

Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning. - Xiao-Yang Liu; Rongyi Zhu; Daochen Zha; Jiechao Gao; Shan Zhong; Meikang Qiu (CoRR, 2023)

In-Processing Modeling Techniques for Machine Learning Fairness: A Survey. - Mingyang Wan; Daochen Zha; Ninghao Liu; Na Zou 001 (ACM Trans. Knowl. Discov. Data, 2023)

Modality-Aware Integration with Large Language Models for Knowledge-Based Visual Question Answering. - Junnan Dong; Qinggang Zhang; Huachi Zhou; Daochen Zha; Pai Zheng; Xiao Huang 001 (ACL (1), 2024)

Customized FinGPT Search Agents Using Foundation Models. - Felix Tian; Ajay Byadgi; Daniel S. Kim; Daochen Zha; Matt White; Kairong Xiao; Xiao-Yang Liu (ICAIF, 2024)

Denoising-Aware Contrastive Learning for Noisy Time Series. - Shuang Zhou 012; Daochen Zha; Xiao Shen 001; Xiao Huang 001; Rui Zhang 028; Korris Fu-Lai Chung (IJCAI, 2024)

Enhanced DouDiZhu Card Game Strategy Using Oracle Guiding and Adaptive Deep Monte Carlo Method. - Qian Luo; Tien Ping Tan; Daochen Zha; Tianqiao Zhang (IJCAI, 2024)

GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models. - Yi Fang; Dongzhe Fan; Daochen Zha; Qiaoyu Tan (KDD, 2024)

Cost-efficient Knowledge-based Question Answering with Large Language Models. - Junnan Dong; Qinggang Zhang; Chuang Zhou 002; Hao Chen 062; Daochen Zha; Xiao Huang 001 (NeurIPS, 2024)

KnowGPT: Knowledge Graph based Prompting for Large Language Models. - Qinggang Zhang; Junnan Dong; Hao Chen 062; Daochen Zha; Zailiang Yu; Xiao Huang 001 (NeurIPS, 2024)

DCAI: Data-centric Artificial Intelligence. - Wei Jin 009; Haohan Wang; Daochen Zha; Qiaoyu Tan; Yao Ma 001; Sharon Li 001; Su-In Lee (WWW (Companion Volume), 2024)

E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classification. - Xin Zhang 104; Daochen Zha; Qiaoyu Tan (CoRR, 2024)

GraphFM: A Comprehensive Benchmark for Graph Foundation Model. - Yuhao Xu; Xinqi Liu; Keyu Duan; Yi Fang; Yu-Neng Chuang; Daochen Zha; Qiaoyu Tan (CoRR, 2024)

Understanding Different Design Choices in Training Large Time Series Models. - Yu-Neng Chuang; Songchen Li; Jiayi Yuan 001; Guanchu Wang; Kwei-Herng Lai; Leisheng Yu; Sirui Ding; Chia-Yuan Chang 002; Qiaoyu Tan; Daochen Zha; Xia Hu 001 (CoRR, 2024)

Large Language Models for Disease Diagnosis: A Scoping Review. - Shuang Zhou 012; Zidu Xu; Mian Zhang; Chunpu Xu; Yawen Guo; Zaifu Zhan; Sirui Ding; Jiashuo Wang; Kaishuai Xu; Yi Fang; Liqiao Xia; Jeremy Yeung; et al. (CoRR, 2024)

Customized FinGPT Search Agents Using Foundation Models. - Felix Tian; Ajay Byadgi; Daniel S. Kim; Daochen Zha; Matt White; Kairong Xiao; Xiaoyang Li 001 (CoRR, 2024)

Dynamic datasets and market environments for financial reinforcement learning. - Xiao-Yang Liu; Ziyi Xia; Hongyang Yang; Jiechao Gao; Daochen Zha; Ming Zhu 002; Christina Dan Wang; Zhaoran Wang 001; Jian Guo (Mach. Learn., 2024)

MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations. - Shaochen (Henry) Zhong; Yifan Lu; Lize Shao; Bhargav Bhushanam; Xiaocong Du; Yixin Wan; Yucheng Shi; Daochen Zha; Yiwei Wang; Ninghao Liu; Kaixiong Zhou; Shuai Xu; et al. (ICLR, 2025)

Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning. - Xiao-Yang Liu; Rongyi Zhu; Daochen Zha; Jiechao Gao; Shan Zhong; Matt White; Meikang Qiu (ACM Trans. Manag. Inf. Syst., 2025)

Beyond Pairwise Learning-To-Rank At Airbnb. - Malay Haldar; Daochen Zha; Huiji Gao; Liwei He; Sanjeev Katariya (CoRR, 2025)

FinLoRA: Benchmarking LoRA Methods for Fine-Tuning LLMs on Financial Datasets. - Dannong Wang; Jaisal Patel; Daochen Zha; Steve Y. Yang; Xiao-Yang Liu (CoRR, 2025)

Data-centric Artificial Intelligence: A Survey. - Daochen Zha; Zaid Pervaiz Bhat; Kwei-Herng Lai; Fan Yang 023; Zhimeng Jiang; Shaochen Zhong; Xia Ben Hu (ACM Comput. Surv., 2025)

Graph-MLLM: Harnessing Multimodal Large Language Models for Multimodal Graph Learning. - Jiajin Liu; Dongzhe Fan; Jiacheng Shen; Chuanhao Ji; Daochen Zha; Qiaoyu Tan (CoRR, 2025)