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Journal Articles
- 2024
[j11]Shengyu Feng
, Baoyu Jing, Yada Zhu, Hanghang Tong:
ArieL: Adversarial Graph Contrastive Learning. ACM Trans. Knowl. Discov. Data 18(4): 82:1-82:22 (2024)- 2018
- [j10]Pei Yang, Qi Tan, Yada Zhu, Jingrui He:
Heterogeneous representation learning with separable structured sparsity regularization. Knowl. Inf. Syst. 55(3): 671-694 (2018) - 2016
- [j9]Yada Zhu, Jingrui He:
Co-Clustering Structural Temporal Data with Applications to Semiconductor Manufacturing. ACM Trans. Knowl. Discov. Data 10(4): 43:1-43:18 (2016) - [j8]Pei Yang, Hasan Davulcu, Yada Zhu, Jingrui He:
A Generalized Hierarchical Multi-Latent Space Model for Heterogeneous Learning. IEEE Trans. Knowl. Data Eng. 28(12): 3154-3168 (2016) - 2015
- [j7]Yada Zhu, Jingrui He, Richard D. Lawrence:
A general framework for predictive tensor modeling with domain knowledge. Data Min. Knowl. Discov. 29(6): 1709-1732 (2015) - [j6]Dzung T. Phan, Yada Zhu:
Multi-stage optimization for periodic inspection planning of geo-distributed infrastructure systems. Eur. J. Oper. Res. 245(3): 797-804 (2015) - 2014
- [j5]Yada Zhu, Emmanuel Yashchin, Jonathan R. M. Hosking:
Parametric Estimation for Window Censored Recurrence Data. Technometrics 56(1): 55-66 (2014) - 2011
- [j4]Yada Zhu, Mingyu Li, Christina M. Young, Minge Xie, Elsayed A. Elsayed:
Impact of measurement error on container inspection policies at port-of-entry. Ann. Oper. Res. 187(1): 23-43 (2011) - 2010
- [j3]Yada Zhu, Elsayed A. Elsayed, Haitao Liao, Ling-Yau Chan:
Availability optimization of systems subject to competing risk. Eur. J. Oper. Res. 202(3): 781-788 (2010) - [j2]Christina M. Young, Mingyu Li, Yada Zhu, Minge Xie, Elsayed A. Elsayed, T. Asamov:
Multiobjective Optimization of a Port-of-Entry Inspection Policy. IEEE Trans Autom. Sci. Eng. 7(2): 392-400 (2010) - 2009
- [j1]Elsayed A. Elsayed, Christina M. Young, Minge Xie, Hao Zhang, Yada Zhu:
Port-of-Entry Inspection: Sensor Deployment Policy Optimization. IEEE Trans Autom. Sci. Eng. 6(2): 265-276 (2009)
Conference and Workshop Papers
- 2024
- [c40]Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong:
Sterling: Synergistic Representation Learning on Bipartite Graphs. AAAI 2024: 12976-12984 - [c39]Junmo Kang, Hongyin Luo, Yada Zhu, Jacob A. Hansen, James R. Glass, David D. Cox, Alan Ritter, Rogério Feris, Leonid Karlinsky:
Self-Specialization: Uncovering Latent Expertise within Large Language Models. ACL (Findings) 2024: 2681-2706 - [c38]Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He:
Fairgen: Towards Fair Graph Generation. ICDE 2024: 2285-2297 - [c37]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. ICLR 2024 - [c36]Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li:
Adversarial Attacks on Fairness of Graph Neural Networks. ICLR 2024 - [c35]Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong:
Class-Imbalanced Graph Learning without Class Rebalancing. ICML 2024 - [c34]Asterios Tsiourvas, Wei Sun, Georgia Perakis, Pin-Yu Chen, Yada Zhu:
Learning Optimal Projection for Forecast Reconciliation of Hierarchical Time Series. ICML 2024 - [c33]Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong:
AIM: Attributing, Interpreting, Mitigating Data Unfairness. KDD 2024: 2014-2025 - [c32]Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou:
Mastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization. KDD 2024: 3045-3056 - [c31]Yue Zhou, Yada Zhu, Diego Antognini, Yoon Kim, Yang Zhang:
Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models. NAACL-HLT 2024: 2793-2804 - 2023
- [c30]Shuaicheng Zhang, Yada Zhu, Dawei Zhou:
TGEditor: Task-Guided Graph Editing for Augmenting Temporal Financial Transaction Networks. ICAIF 2023: 219-226 - [c29]Zixuan Yuan, Yada Zhu, Wei Zhang, Hui Xiong:
Earnings Call Analysis Using a Sparse Attention Based Encoder and Multi-Source Counterfactual Augmentation. ICAIF 2023: 331-339 - [c28]Wenyu Chen, Riade Benbaki, Yada Zhu, Rahul Mazumder:
Dynamic Covariance Estimation under Structural Assumptions via a Joint Optimization Approach. ICAIF 2023: 445-453 - [c27]Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew Margenot, Hanghang Tong:
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders. KDD 2023: 2256-2268 - [c26]Lecheng Zheng, Yada Zhu, Jingrui He:
Fairness-aware Multi-view Clustering. SDM 2023: 856-864 - 2022
- [c25]Di Chen, Yada Zhu, Miao Liu, Jianbo Li:
Cost-Efficient Reinforcement Learning for Optimal Trade Execution on Dynamic Market Environment. ICAIF 2022: 386-393 - [c24]Shibal Ibrahim, Wenyu Chen, Yada Zhu, Pin-Yu Chen, Yang Zhang, Rahul Mazumder:
Knowledge Graph Guided Simultaneous Forecasting and Network Learning for Multivariate Financial Time Series. ICAIF 2022: 480-488 - [c23]Lecheng Zheng, Jinjun Xiong, Yada Zhu, Jingrui He:
Contrastive Learning with Complex Heterogeneity. KDD 2022: 2594-2604 - [c22]Yaojing Wang, Yuan Yao, Feng Xu, Yada Zhu, Hanghang Tong:
Structure Meets Sequences: Predicting Network of Co-evolving Sequences. WSDM 2022: 1090-1098 - [c21]Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong:
Adversarial Graph Contrastive Learning with Information Regularization. WWW 2022: 1362-1371 - 2021
- [c20]Jorge L. C. Sanz, Yada Zhu:
Toward Scalable Artificial Intelligence in Finance. SCC 2021: 460-469 - [c19]Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He:
Outlier Impact Characterization for Time Series Data. AAAI 2021: 11595-11603 - [c18]Wei Zhang, Ziming Huang, Yada Zhu, Guangnan Ye, Xiaodong Cui, Fan Zhang:
On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation. ACL/IJCNLP (1) 2021: 5399-5411 - [c17]Yada Zhu, Wenyu Chen, Yang Zhang, Tian Gao, Jianbo Li:
Probabilistic framework for modeling event shocks to financial time series. ICAIF 2021: 42:1-42:8 - [c16]Baoyu Jing, Hanghang Tong, Yada Zhu:
Network of Tensor Time Series. WWW 2021: 2425-2437 - 2020
- [c15]Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Ju Xiao, Bo Li:
Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States. AAAI 2020: 1112-1119 - [c14]Zhining Liu, Dawei Zhou, Yada Zhu, Jinjie Gu, Jingrui He:
Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk. AAAI 2020: 4973-4980 - [c13]Di Chen, Yada Zhu, Xiaodong Cui, Carla P. Gomes:
Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance. IJCAI 2020: 4476-4482 - [c12]Dawei Zhou, Lecheng Zheng, Yada Zhu, Jianbo Li, Jingrui He:
Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting. WWW 2020: 2230-2240 - 2019
- [c11]Rui Zhang, Hanghang Tong, Yinglong Xia, Yada Zhu:
Robust Embedded Deep K-means Clustering. CIKM 2019: 1181-1190 - 2018
- [c10]Yada Zhu, Jianbo Li, Jingrui He, Brian Leo Quanz, Ajay A. Deshpande:
A Local Algorithm for Product Return Prediction in E-Commerce. IJCAI 2018: 3718-3724 - [c9]Jianbo Li, Jingrui He, Yada Zhu:
E-tail Product Return Prediction via Hypergraph-based Local Graph Cut. KDD 2018: 519-527 - 2017
- [c8]Jianbo Li, Jingrui He, Yada Zhu:
HiMuV: Hierarchical Framework for Modeling Multi-modality Multi-resolution Data. ICDM 2017: 267-276 - [c7]Hongxia Yang, Yada Zhu, Jingrui He:
Local Algorithm for User Action Prediction Towards Display Ads. KDD 2017: 2091-2099 - [c6]Yada Zhu, Jianbo Li, Jingrui He:
Learning from Multi-Modality Multi-Resolution Data: an Optimization Approach. SDM 2017: 714-722 - 2015
- [c5]Yada Zhu, Jinjun Xiong:
Modern Big Data Analytics for "Old-fashioned" Semiconductor Industry Applications. ICCAD 2015: 776-780 - [c4]Yada Zhu, Hongxia Yang, Jingrui He:
Co-Clustering based Dual Prediction for Cargo Pricing Optimization. KDD 2015: 1583-1592 - 2014
- [c3]Yada Zhu, Jingrui He:
Co-Clustering Structural Temporal Data with Applications to Semiconductor Manufacturing. ICDM 2014: 1121-1126 - 2012
- [c2]Yada Zhu, Jingrui He, Rick Lawrence:
Hierarchical Modeling with Tensor Inputs. AAAI 2012: 1233-1239 - [c1]Jingrui He, Yada Zhu:
Hierarchical Multi-task Learning with Application to Wafer Quality Prediction. ICDM 2012: 290-298
Reference Works
- 2018
- [r2]Yada Zhu, Jingrui He:
Social Phishing. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - 2014
- [r1]Jingrui He, Yada Zhu:
Social Engineering/Phishing. Encyclopedia of Social Network Analysis and Mining 2014: 1777-1783
Informal and Other Publications
- 2024
- [i23]Yue Zhou, Yada Zhu, Diego Antognini, Yoon Kim, Yang Zhang:
Paraphrase and Solve: Exploring and Exploiting the Impact of Surface Form on Mathematical Reasoning in Large Language Models. CoRR abs/2404.11500 (2024) - [i22]Yikun Ban, Ishika Agarwal, Ziwei Wu, Yada Zhu, Kommy Weldemariam, Hanghang Tong, Jingrui He:
Neural Active Learning Beyond Bandits. CoRR abs/2404.12522 (2024) - [i21]Zhining Liu, Ruizhong Qiu, Zhichen Zeng, Yada Zhu, Hendrik F. Hamann, Hanghang Tong:
AIM: Attributing, Interpreting, Mitigating Data Unfairness. CoRR abs/2406.08819 (2024) - [i20]Junhong Lin, Xiaojie Guo, Shuaicheng Zhang, Dawei Zhou, Yada Zhu, Julian Shun:
When Heterophily Meets Heterogeneity: New Graph Benchmarks and Effective Methods. CoRR abs/2407.10916 (2024) - [i19]Dongqi Fu, Yada Zhu, Hanghang Tong, Kommy Weldemariam, Onkar Bhardwaj, Jingrui He:
Generating Fine-Grained Causality in Climate Time Series Data for Forecasting and Anomaly Detection. CoRR abs/2408.04254 (2024) - 2023
- [i18]Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong:
STERLING: Synergistic Representation Learning on Bipartite Graphs. CoRR abs/2302.05428 (2023) - [i17]Lecheng Zheng, Yada Zhu, Jingrui He:
Fairness-aware Multi-view Clustering. CoRR abs/2302.05788 (2023) - [i16]Lecheng Zheng, Dawei Zhou, Hanghang Tong, Jiejun Xu, Yada Zhu, Jingrui He:
FairGen: Towards Fair Graph Generation. CoRR abs/2303.17743 (2023) - [i15]Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Dawei Zhou:
Characterizing Long-Tail Categories on Graphs. CoRR abs/2305.09938 (2023) - [i14]Dingsu Wang, Yuchen Yan, Ruizhong Qiu, Yada Zhu, Kaiyu Guan, Andrew J. Margenot, Hanghang Tong:
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders. CoRR abs/2305.18612 (2023) - [i13]Zhining Liu, Zhichen Zeng, Ruizhong Qiu, Hyunsik Yoo, David Zhou, Zhe Xu, Yada Zhu, Kommy Weldemariam, Jingrui He, Hanghang Tong:
Topological Augmentation for Class-Imbalanced Node Classification. CoRR abs/2308.14181 (2023) - [i12]Junmo Kang, Hongyin Luo, Yada Zhu, James R. Glass, David D. Cox, Alan Ritter, Rogério Feris, Leonid Karlinsky:
Self-Specialization: Uncovering Latent Expertise within Large Language Models. CoRR abs/2310.00160 (2023) - [i11]Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li:
Adversarial Attacks on Fairness of Graph Neural Networks. CoRR abs/2310.13822 (2023) - 2022
- [i10]Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong:
Adversarial Graph Contrastive Learning with Information Regularization. CoRR abs/2202.06491 (2022) - [i9]Baoyu Jing, Yuchen Yan, Yada Zhu, Hanghang Tong:
COIN: Co-Cluster Infomax for Bipartite Graphs. CoRR abs/2206.00006 (2022) - [i8]Shengyu Feng, Baoyu Jing, Yada Zhu, Hanghang Tong:
ARIEL: Adversarial Graph Contrastive Learning. CoRR abs/2208.06956 (2022) - [i7]Baoyu Jing, Si Zhang, Yada Zhu, Bin Peng, Kaiyu Guan, Andrew Margenot, Hanghang Tong:
Retrieval Based Time Series Forecasting. CoRR abs/2209.13525 (2022) - 2021
- [i6]Baoyu Jing, Hanghang Tong, Yada Zhu:
Network of Tensor Time Series. CoRR abs/2102.07736 (2021) - [i5]Lecheng Zheng, Yada Zhu, Jingrui He, Jinjun Xiong:
Heterogeneous Contrastive Learning. CoRR abs/2105.09401 (2021) - [i4]Wei Zhang, Ziming Huang, Yada Zhu, Guangnan Ye, Xiaodong Cui, Fan Zhang:
On Sample Based Explanation Methods for NLP: Efficiency, Faithfulness, and Semantic Evaluation. CoRR abs/2106.04753 (2021) - [i3]Zixuan Yuan, Yada Zhu, Wei Zhang, Ziming Huang, Guangnan Ye, Hui Xiong:
Multi-Domain Transformer-Based Counterfactual Augmentation for Earnings Call Analysis. CoRR abs/2112.00963 (2021) - 2020
- [i2]Yunan Ye, Hengzhi Pei, Boxin Wang, Pin-Yu Chen, Yada Zhu, Jun Xiao, Bo Li:
Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States. CoRR abs/2002.05780 (2020) - 2019
- [i1]Di Chen, Yada Zhu, Xiaodong Cui, Carla P. Gomes:
Task-Based Learning via Task-Oriented Prediction Network. CoRR abs/1910.09357 (2019)
Coauthor Index
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