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ORCIDXia Ben Hu
Xia (Ben) Hu – Xia Hu 0001
Person information
- affiliation: Rice University, Department of Computer Science, Houston, TX, USA
- affiliation (former): Texas A&M University, Department of Computer Science and Engineering, College Station, TX, USA
- affiliation (PhD): Arizona State University, Department of Computer Science, Tempe, AZ, USA
- affiliation (former): Beihang University, Beijing, China
Other persons with the same name
- Xia Hu — disambiguation page
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2020 – today
- 2024
[j56]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding. Commun. ACM 67(1): 110-120 (2024)- [j55]Ruixiang Tang
, Yu-Neng Chuang, Xia Hu:
The Science of Detecting LLM-Generated Text. Commun. ACM 67(4): 50-59 (2024) - [j54]Zirui Liu, Qingquan Song, Li Li, Soo-Hyun Choi, Rui Chen, Xia Hu:
PME: pruning-based multi-size embedding for recommender systems. Frontiers Big Data 6 (2024) - [j53]Aokun Chen, Yunpeng Zhao, Yi Zheng, Hui Hu, Xia Hu, Jennifer N. Fishe, William R. Hogan, Elizabeth A. Shenkman, Yi Guo, Jiang Bian:
Exploring the Relation between Contextual Social Determinants of Health and COVID-19 Occurrence and Hospitalization. Informatics 11: 4 (2024) - [j52]Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu:
SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization. J. Biomed. Informatics 151: 104606 (2024) - [j51]Sirui Ding, Shenghan Zhang, Xia Hu, Na Zou:
Identify and mitigate bias in electronic phenotyping: A comprehensive study from computational perspective. J. Biomed. Informatics 156: 104671 (2024) - [j50]Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Shaochen Zhong, Bing Yin, Xia Ben Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. ACM Trans. Knowl. Discov. Data 18(6): 160:1-160:32 (2024) - [j49]Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu:
Collaborative Graph Neural Networks for Attributed Network Embedding. IEEE Trans. Knowl. Data Eng. 36(3): 972-986 (2024) - [j48]Tianming Liu, Dajiang Zhu, Fei Wang, Islem Rekik, Xia Ben Hu, Dinggang Shen:
Editorial Special Issue on Explainable and Generalizable Deep Learning for Medical Imaging. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7271-7274 (2024) - [c191]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
Chasing Fairness in Graphs: A GNN Architecture Perspective. AAAI 2024: 21214-21222 - [c190]Jiayi Yuan, Hongyi Liu, Shaochen Zhong, Yu-Neng Chuang, Songchen Li, Guanchu Wang, Duy Le, Hongye Jin, Vipin Chaudhary, Zhaozhuo Xu, Zirui Liu, Xia Ben Hu:
KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches. EMNLP (Findings) 2024: 4623-4648 - [c189]Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang, Shaochen Zhong, Jiayi Yuan, Hongye Jin, Zirui Liu, Vipin Chaudhary, Shuai Xu, James Caverlee, Xia Ben Hu:
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion. EMNLP 2024: 6928-6941 - [c188]Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin:
Unraveling the 'Anomaly' in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. ICDE 2024: 981-994 - [c187]Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu:
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. ICLR 2024 - [c186]Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu:
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning. ICML 2024 - [c185]Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu:
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache. ICML 2024 - [c184]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
TVE: Learning Meta-attribution for Transferable Vision Explainer. ICML 2024 - [c183]Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava:
Soft Prompt Recovers Compressed LLMs, Transferably. ICML 2024 - [c182]Shaochen Zhong, Duy Le, Zirui Liu, Zhimeng Jiang, Andrew Ye, Jiamu Zhang, Jiayi Yuan, Kaixiong Zhou, Zhaozhuo Xu, Jing Ma, Shuai Xu, Vipin Chaudhary, Xia Hu:
GNNs Also Deserve Editing, and They Need It More Than Once. ICML 2024 - [c181]Ruixiang Tang, Yu-Neng Chuang, Xuanting Cai, Mengnan Du, Xia Hu:
Secure Your Model: An Effective Key Prompt Protection Mechanism for Large Language Models. NAACL-HLT (Findings) 2024: 4061-4073 - [c180]Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Ben Hu:
Learning to Compress Prompt in Natural Language Formats. NAACL-HLT 2024: 7756-7767 - [c179]Huiyuan Chen, Vivian Lai, Hongye Jin, Zhimeng Jiang, Mahashweta Das, Xia Hu:
Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering. WSDM 2024: 106-115 - [i153]Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu:
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning. CoRR abs/2401.01325 (2024) - [i152]Zirui Liu, Qingquan Song, Qiang Charles Xiao, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Xia Hu:
FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference. CoRR abs/2401.04044 (2024) - [i151]Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu:
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache. CoRR abs/2402.02750 (2024) - [i150]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Fan Yang, Mengnan Du, Xuanting Cai, Xia Hu:
Large Language Models As Faithful Explainers. CoRR abs/2402.04678 (2024) - [i149]Aokun Chen, Qian Li, Yu Huang, Yongqiu Li, Yu-Neng Chuang, Xia Hu, Serena Guo, Yonghui Wu, Yi Guo, Jiang Bian:
Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data. CoRR abs/2402.15515 (2024) - [i148]Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Hu:
Learning to Compress Prompt in Natural Language Formats. CoRR abs/2402.18700 (2024) - [i147]Hongyi Liu, Zirui Liu, Ruixiang Tang, Jiayi Yuan, Shaochen Zhong, Yu-Neng Chuang, Li Li, Rui Chen, Xia Hu:
LoRA-as-an-Attack! Piercing LLM Safety Under The Share-and-Play Scenario. CoRR abs/2403.00108 (2024) - [i146]Yu-Neng Chuang, Songchen Li, Jiayi Yuan, Guanchu Wang, Kwei-Herng Lai, Leisheng Yu, Sirui Ding, Chia-Yuan Chang, Qiaoyu Tan, Daochen Zha, Xia Hu:
Understanding Different Design Choices in Training Large Time Series Models. CoRR abs/2406.14045 (2024) - [i145]Jiayi Yuan, Hongyi Liu, Shaochen Zhong, Yu-Neng Chuang, Songchen Li, Guanchu Wang, Duy Le, Hongye Jin, Vipin Chaudhary, Zhaozhuo Xu, Zirui Liu, Xia Hu:
KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches. CoRR abs/2407.01527 (2024) - [i144]Guanchu Wang, Junhao Ran, Ruixiang Tang, Chia-Yuan Chang, Yu-Neng Chuang, Zirui Liu, Vladimir Braverman, Zhandong Liu, Xia Hu:
Assessing and Enhancing Large Language Models in Rare Disease Question-answering. CoRR abs/2408.08422 (2024) - [i143]Guanchu Wang, Yu-Neng Chuang, Ruixiang Tang, Shaochen Zhong, Jiayi Yuan, Hongye Jin, Zirui Liu, Vipin Chaudhary, Shuai Xu, James Caverlee, Xia Hu:
Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion. CoRR abs/2410.05331 (2024) - [i142]Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Ben Hu:
Gradient Rewiring for Editable Graph Neural Network Training. CoRR abs/2410.15556 (2024) - 2023
- [j47]Zhaoyi Chen, Yuchen Yang, Dazheng Zhang, Jingchuan Guo, Yi Guo, Xia Hu, Yong Chen, Jiang Bian:
Predicting the Risk of Alzheimer's Disease and Related Dementia in Patients with Mild Cognitive Impairment Using a Semi-Competing Risk Approach. Informatics 10(2): 46 (2023) - [j46]Can Li, Sirui Ding, Na Zou, Xia Hu, Xiaoqian Jiang, Kai Zhang:
Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling. J. Biomed. Informatics 143: 104399 (2023) - [j45]Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang:
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2769-2781 (2023) - [j44]Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu:
Did You Train on My Dataset? Towards Public Dataset Protection with CleanLabel Backdoor Watermarking. SIGKDD Explor. 25(1): 43-53 (2023) - [j43]Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi:
Adaptive RiskAware Bidding with Budget Constraint in Display Advertising. SIGKDD Explor. 25(1): 73-82 (2023) - [j42]Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu:
Retiring ΔDP: New Distribution-Level Metrics for Demographic Parity. Trans. Mach. Learn. Res. 2023 (2023) - [j41]Zirui Liu, Kaixiong Zhou, Zhimeng Jiang, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
DSpar: An Embarrassingly Simple Strategy for Efficient GNN training and inference via Degree-based Sparsification. Trans. Mach. Learn. Res. 2023 (2023) - [c178]Qizhang Feng, Jiayi Yuan, Forhan Bin Emdad, Karim Hanna, Xia Hu, Zhe He:
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke. BCB 2023: 26:1-26:6 - [c177]Kwei-Herng Lai, Daochen Zha, Huiyuan Chen, Mangesh Bendre, Yuzhong Chen, Mahashweta Das, Hao Yang, Xia Hu:
Tackling Diverse Minorities in Imbalanced Classification. CIKM 2023: 1178-1187 - [c176]Ruixiang Tang, Hongye Jin, Mengnan Du, Curtis Wigington, Rajiv Jain, Xia Hu:
Exposing Model Theft: A Robust and Transferable Watermark for Thwarting Model Extraction Attacks. CIKM 2023: 4315-4319 - [c175]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Hu:
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CIKM 2023: 5021-5025 - [c174]Mengnan Du, Subhabrata Mukherjee, Yu Cheng, Milad Shokouhi, Xia Hu, Ahmed Hassan Awadallah:
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding. EACL 2023: 1758-1770 - [c173]Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan Kulkarni, Xia Hu:
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks. EMNLP (Findings) 2023: 15406-15418 - [c172]Yezi Liu, Qinggang Zhang, Mengnan Du, Xiao Huang, Xia Hu:
Error Detection on Knowledge Graphs with Triple Embedding. EUSIPCO 2023: 1604-1608 - [c171]Andrew T. Lian, Alfredo Costilla-Reyes, Xia Hu:
CAPTAIN: An AI-Based Chatbot for Cyberbullying Prevention and Intervention. HCI (41) 2023: 98-107 - [c170]Qiaoyu Tan, Daochen Zha, Ninghao Liu, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu:
Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation. ICDM 2023: 1343-1348 - [c169]Shenghan Zhang, Haoxuan Li, Ruixiang Tang, Sirui Ding, Laila Rasmy, Degui Zhi, Na Zou, Xia Hu:
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. ICHI 2023: 268-275 - [c168]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
CoRTX: Contrastive Framework for Real-time Explanation. ICLR 2023 - [c167]Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah:
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. ICLR 2023 - [c166]Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu:
RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations. ICML 2023: 21951-21968 - [c165]Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu:
DIVISION: Memory Efficient Training via Dual Activation Precision. ICML 2023: 36036-36057 - [c164]Huiyuan Chen, Kaixiong Zhou, Zhimeng Jiang, Chin-Chia Michael Yeh, Xiaoting Li, Menghai Pan, Yan Zheng, Xia Hu, Hao Yang:
Probabilistic Masked Attention Networks for Explainable Sequential Recommendation. IJCAI 2023: 2068-2076 - [c163]Yue Xu, Hao Chen, Zefan Wang, Jianwen Yin, Qijie Shen, Dimin Wang, Feiran Huang, Lixiang Lai, Tao Zhuang, Junfeng Ge, Xia Hu:
Multi-factor Sequential Re-ranking with Perception-Aware Diversification. KDD 2023: 5327-5337 - [c162]Daochen Zha, Kwei-Herng Lai, Fan Yang, Na Zou, Huiji Gao, Xia Hu:
Data-centric AI: Techniques and Future Perspectives. KDD 2023: 5839-5840 - [c161]Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu:
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. MLSys 2023 - [c160]Qizhang Feng, Zhimeng Stephen Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu:
Fair Graph Distillation. NeurIPS 2023 - [c159]Zhimeng Stephen Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu:
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach. NeurIPS 2023 - [c158]Zirui Liu, Guanchu Wang, Shaochen (Henry) Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang (Ryan) Tang, Zhimeng Stephen Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu:
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. NeurIPS 2023 - [c157]Ruixiang (Ryan) Tang, Jiayi Yuan, Yiming Li, Zirui Liu, Rui Chen, Xia Hu:
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots. NeurIPS 2023 - [c156]Shaochen (Henry) Zhong, Zaichuan You, Jiamu Zhang, Sebastian Zhao, Zachary LeClaire, Zirui Liu, Daochen Zha, Vipin Chaudhary, Shuai Xu, Xia Hu:
One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning. NeurIPS 2023 - [c155]Ruixiang Tang, Mengnan Du, Xia Hu:
Deep Serial Number: Computational Watermark for DNN Intellectual Property Protection. ECML/PKDD (6) 2023: 157-173 - [c154]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. ECML/PKDD (2) 2023: 241-258 - [c153]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang:
Hessian-aware Quantized Node Embeddings for Recommendation. RecSys 2023: 757-762 - [c152]Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu:
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. SDM 2023: 55-63 - [c151]Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. SDM 2023: 676-684 - [c150]Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Xia Hu:
Data-centric AI: Perspectives and Challenges. SDM 2023: 945-948 - [c149]Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection. WSDM 2023: 625-633 - [c148]Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu:
S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking. WSDM 2023: 787-795 - [i141]Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Xia Hu:
Data-centric AI: Perspectives and Challenges. CoRR abs/2301.04819 (2023) - [i140]Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu:
Retiring $Δ$DP: New Distribution-Level Metrics for Demographic Parity. CoRR abs/2301.13443 (2023) - [i139]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Zirui Liu, Xuanting Cai, Mengnan Du, Xia Ben Hu:
Efficient XAI Techniques: A Taxonomic Survey. CoRR abs/2302.03225 (2023) - [i138]Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu:
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. CoRR abs/2302.09400 (2023) - [i137]Diego Martinez, Daochen Zha, Qiaoyu Tan, Xia Hu:
Towards Personalized Preprocessing Pipeline Search. CoRR abs/2302.14329 (2023) - [i136]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
CoRTX: Contrastive Framework for Real-time Explanation. CoRR abs/2303.02794 (2023) - [i135]Zhimeng Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Na Zou, Xia Ben Hu:
Weight Perturbation Can Help Fairness under Distribution Shift. CoRR abs/2303.03300 (2023) - [i134]Ruixiang Tang, Xiaotian Han, Xiaoqian Jiang, Xia Hu:
Does Synthetic Data Generation of LLMs Help Clinical Text Mining? CoRR abs/2303.04360 (2023) - [i133]Ruixiang Tang, Yu-Neng Chuang, Xia Hu:
The Science of Detecting LLM-Generated Texts. CoRR abs/2303.07205 (2023) - [i132]Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, Xia Hu:
Data-centric Artificial Intelligence: A Survey. CoRR abs/2303.10158 (2023) - [i131]Shenghan Zhang, Haoxuan Li, Ruixiang Tang, Sirui Ding, Laila Rasmy, Degui Zhi, Na Zou, Xia Hu:
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. CoRR abs/2303.10794 (2023) - [i130]Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu:
Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking. CoRR abs/2303.11470 (2023) - [i129]Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu:
SPeC: A Soft Prompt-Based Calibration on Mitigating Performance Variability in Clinical Notes Summarization. CoRR abs/2303.13035 (2023) - [i128]Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu, Na Zou:
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint. CoRR abs/2303.13790 (2023) - [i127]Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, Xia Hu:
LLM for Patient-Trial Matching: Privacy-Aware Data Augmentation Towards Better Performance and Generalizability. CoRR abs/2303.16756 (2023) - [i126]Sirui Ding, Qiaoyu Tan, Chia-Yuan Chang, Na Zou, Kai Zhang, Nathan R. Hoot, Xiaoqian Jiang, Xia Hu:
Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant. CoRR abs/2304.00012 (2023) - [i125]Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. CoRR abs/2304.07453 (2023) - [i124]Guanchu Wang, Ninghao Liu, Daochen Zha, Xia Ben Hu:
Interactive System-wise Anomaly Detection. CoRR abs/2304.10704 (2023) - [i123]Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. CoRR abs/2304.13712 (2023) - [i122]Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu:
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. CoRR abs/2305.01868 (2023) - [i121]Zhaozhuo Xu, Zirui Liu, Beidi Chen, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava:
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt. CoRR abs/2305.11186 (2023) - [i120]Yue Xu, Hao Chen, Zefan Wang, Jianwen Yin, Qijie Shen, Dimin Wang, Feiran Huang, Lixiang Lai, Tao Zhuang, Junfeng Ge, Xia Hu:
Multi-factor Sequential Re-ranking with Perception-Aware Diversification. CoRR abs/2305.12420 (2023) - [i119]Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu:
DEGREE: Decomposition Based Explanation For Graph Neural Networks. CoRR abs/2305.12895 (2023) - [i118]Zirui Liu, Guanchu Wang, Shaochen Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang Tang, Zhimeng Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Ben Hu:
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. CoRR abs/2305.15265 (2023) - [i117]Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
Editable Graph Neural Network for Node Classifications. CoRR abs/2305.15529 (2023) - [i116]Yao Rong, Guanchu Wang, Qizhang Feng, Ninghao Liu, Zirui Liu, Enkelejda Kasneci, Xia Ben Hu:
Efficient GNN Explanation via Learning Removal-based Attribution. CoRR abs/2306.05760 (2023) - [i115]Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu:
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. CoRR abs/2306.09468 (2023) - [i114]Chia-Yuan Chang, Yu-Neng Chuang, Kwei-Herng Lai, Xiaotian Han, Xia Hu, Na Zou:
Towards Assumption-free Bias Mitigation. CoRR abs/2307.04105 (2023) - [i113]Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu:
Collaborative Graph Neural Networks for Attributed Network Embedding. CoRR abs/2307.11981 (2023) - [i112]Qizhang Feng, Jiayi Yuan, Forhan Bin Emdad, Karim Hanna, Xia Hu, Zhe He:
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke. CoRR abs/2308.05110 (2023) - [i111]Kwei-Herng Lai, Daochen Zha, Huiyuan Chen, Mangesh Bendre, Yuzhong Chen, Mahashweta Das, Hao Yang, Xia Hu:
Tackling Diverse Minorities in Imbalanced Classification. CoRR abs/2308.14838 (2023) - [i110]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang:
Hessian-aware Quantized Node Embeddings for Recommendation. CoRR abs/2309.01032 (2023) - [i109]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Ben Hu:
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CoRR abs/2309.01808 (2023) - [i108]Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu:
On the Equivalence of Graph Convolution and Mixup. CoRR abs/2310.00183 (2023) - [i107]Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Chia-Yuan Chang, Xia Hu:
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length. CoRR abs/2310.00576 (2023) - [i106]Ruixiang Tang, Gord Lueck, Rodolfo Quispe, Huseyin A. Inan, Janardhan Kulkarni, Xia Hu:
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks. CoRR abs/2310.13291 (2023) - [i105]Ruixiang Tang, Jiayi Yuan, Yiming Li, Zirui Liu, Rui Chen, Xia Hu:
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots. CoRR abs/2310.18633 (2023) - [i104]Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin:
Unraveling the "Anomaly" in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. CoRR abs/2311.11235 (2023) - [i103]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
Chasing Fairness in Graphs: A GNN Architecture Perspective. CoRR abs/2312.12369 (2023) - [i102]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
LETA: Learning Transferable Attribution for Generic Vision Explainer. CoRR abs/2312.15359 (2023) - [i101]Huiyuan Chen, Vivian Lai, Hongye Jin, Zhimeng Jiang, Mahashweta Das, Xia Hu:
Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering. CoRR abs/2312.17468 (2023) - 2022
- [j40]Ruixiang Tang, Ninghao Liu, Fan Yang, Na Zou, Xia Hu:
Defense Against Explanation Manipulation. Frontiers Big Data 5: 704203 (2022) - [j39]Kaixiong Zhou, Xiao Huang, Qingquan Song, Rui Chen, Xia Hu:
Auto-GNN: Neural architecture search of graph neural networks. Frontiers Big Data 5 (2022) - [j38]Hao Yuan, Lei Cai, Xia Hu, Jie Wang, Shuiwang Ji:
Interpreting Image Classifiers by Generating Discrete Masks. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2019-2030 (2022) - [j37]Weijie Fu, Meng Wang, Mengnan Du, Ninghao Liu, Shijie Hao, Xia Hu:
Differentiated Explanation of Deep Neural Networks With Skewed Distributions. IEEE Trans. Pattern Anal. Mach. Intell. 44(6): 2909-2922 (2022) - [j36]Imtiaz Ahmed, Travis Galoppo, Xia Ben Hu, Yu Ding:
Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection. IEEE Trans. Pattern Anal. Mach. Intell. 44(8): 4110-4124 (2022) - [j35]Fangsheng Wu, Mengnan Du, Chao Fan, Ruixiang Tang, Yang Yang, Ali Mostafavi, Xia Hu:
Understanding Social Biases Behind Location Names in Contextual Word Embedding Models. IEEE Trans. Comput. Soc. Syst. 9(2): 458-468 (2022) - [j34]Hongxu Chen, Hongzhi Yin, Tong Chen, Weiqing Wang, Xue Li, Xia Hu:
Social Boosted Recommendation With Folded Bipartite Network Embedding. IEEE Trans. Knowl. Data Eng. 34(2): 914-926 (2022) - [j33]Jiaxu Cui, Bo Yang, Bingyi Sun, Xia Hu, Jiming Liu:
Scalable and Parallel Deep Bayesian Optimization on Attributed Graphs. IEEE Trans. Neural Networks Learn. Syst. 33(1): 103-116 (2022) - [j32]Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu:
Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2365-2377 (2022) - [j31]Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu:
Subarchitecture Ensemble Pruning in Neural Architecture Search. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7928-7936 (2022) - [c147]Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang:
Orthogonal Graph Neural Networks. AAAI 2022: 3996-4004 - [c146]Mengnan Du, Ruixiang Tang, Weijie Fu, Xia Hu:
Towards Debiasing DNN Models from Spurious Feature Influence. AAAI 2022: 9521-9528 - [c145]Zhuoer Wang, Qizhang Feng, Mohinish Chatterjee, Xing Zhao, Yezi Liu, Yuening Li, Abhay Kumar Singh, Frank M. Shipman, Xia Hu, James Caverlee:
RES: An Interpretable Replicability Estimation System for Research Publications. AAAI 2022: 13230-13232 - [c144]Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu:
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. AMIA 2022 - [c143]David E. Hubbard, Sierra Laddusaw, Qiaoyu Tan, Xia Hu:
Analysis Of Acknowledgments of Libraries in the Journal Literature Using Machine Learning. ASIST 2022: 709-711 - [c142]Duc N. M. Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks. AutoML 2022: 4/1-16 - [c141]Daochen Zha, Kwei-Herng Lai, Qiaoyu Tan, Sirui Ding, Na Zou, Xia Ben Hu:
Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning. CIKM 2022: 2476-2485 - [c140]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:
BED: A Real-Time Object Detection System for Edge Devices. CIKM 2022: 4994-4998 - [c139]Zhou Yang, Ninghao Liu, Xia Ben Hu, Fang Jin:
Tutorial on Deep Learning Interpretation: A Data Perspective. CIKM 2022: 5156-5159 - [c138]Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu:
DEGREE: Decomposition Based Explanation for Graph Neural Networks. ICLR 2022 - [c137]Zhimeng Jiang, Xiaotian Han, Chao Fan, Fan Yang, Ali Mostafavi, Xia Hu:
Generalized Demographic Parity for Group Fairness. ICLR 2022 - [c136]Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
An Information Fusion Approach to Learning with Instance-Dependent Label Noise. ICLR 2022 - [c135]Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu:
EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression. ICLR 2022 - [c134]Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu:
G-Mixup: Graph Data Augmentation for Graph Classification. ICML 2022: 8230-8248 - [c133]Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
Accelerating Shapley Explanation via Contributive Cooperator Selection. ICML 2022: 22576-22590 - [c132]Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Table2Graph: Transforming Tabular Data to Unified Weighted Graph. IJCAI 2022: 2420-2426 - [c131]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, Xia Hu:
AutoVideo: An Automated Video Action Recognition System. IJCAI 2022: 5952-5955 - [c130]Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Jingchao Ni, Denghui Zhang, Haifeng Chen, Xia Hu:
Towards Learning Disentangled Representations for Time Series. KDD 2022: 3270-3278 - [c129]Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. KDD 2022: 4461-4471 - [c128]Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. NeurIPS 2022 - [c127]Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu:
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. NeurIPS 2022 - [c126]Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang:
TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems. RecSys 2022: 257-267 - [c125]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Towards Similarity-Aware Time-Series Classification. SDM 2022: 199-207 - [c124]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Xia Hu, Fei Wang, Hao Yang:
Adversarial Graph Perturbations for Recommendations at Scale. SIGIR 2022: 1854-1858 - [c123]Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu:
Geometric Graph Representation Learning via Maximizing Rate Reduction. WWW 2022: 1226-1237 - [i100]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Towards Similarity-Aware Time-Series Classification. CoRR abs/2201.01413 (2022) - [i99]Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen, Soo-Hyun Choi, Xia Hu:
MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs. CoRR abs/2201.02534 (2022) - [i98]Ying-Xin Wu, Xiang Wang, An Zhang, Xia Hu, Fuli Feng, Xiangnan He, Tat-Seng Chua:
Deconfounding to Explanation Evaluation in Graph Neural Networks. CoRR abs/2201.08802 (2022) - [i97]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
FMP: Toward Fair Graph Message Passing against Topology Bias. CoRR abs/2202.04187 (2022) - [i96]Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu:
Geometric Graph Representation Learning via Maximizing Rate Reduction. CoRR abs/2202.06241 (2022) - [i95]Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu:
G-Mixup: Graph Data Augmentation for Graph Classification. CoRR abs/2202.07179 (2022) - [i94]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:
BED: A Real-Time Object Detection System for Edge Devices. CoRR abs/2202.07503 (2022) - [i93]Yicheng Wang, Xiaotian Han, Chia-Yuan Chang, Daochen Zha, Ulisses Braga-Neto, Xia Hu:
Auto-PINN: Understanding and Optimizing Physics-Informed Neural Architecture. CoRR abs/2205.13748 (2022) - [i92]Guanchu Wang, Yu-Neng Chuang, Mengnan Du, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
Accelerating Shapley Explanation via Contributive Cooperator Selection. CoRR abs/2206.08529 (2022) - [i91]Qizhang Feng, Mengnan Du, Na Zou, Xia Hu:
Fair Machine Learning in Healthcare: A Review. CoRR abs/2206.14397 (2022) - [i90]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. CoRR abs/2207.10018 (2022) - [i89]Fan Yang, Qizhang Feng, Kaixiong Zhou, Jiahao Chen, Xia Hu:
Differentially Private Counterfactuals via Functional Mechanism. CoRR abs/2208.02878 (2022) - [i88]Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu:
Towards Memory Efficient Training via Dual Activation Precision. CoRR abs/2208.04187 (2022) - [i87]Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. CoRR abs/2208.06399 (2022) - [i86]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey. CoRR abs/2208.11857 (2022) - [i85]Daochen Zha, Kwei-Herng Lai, Qiaoyu Tan, Sirui Ding, Na Zou, Xia Ben Hu:
Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning. CoRR abs/2208.12433 (2022) - [i84]Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah:
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. CoRR abs/2210.00102 (2022) - [i83]Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu:
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. CoRR abs/2210.02023 (2022) - [i82]Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang:
A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking. CoRR abs/2210.07494 (2022) - [i81]Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu:
RSC: Accelerating Graph Neural Networks Training via Randomized Sparse Computations. CoRR abs/2210.10737 (2022) - [i80]Kaixiong Zhou, Zhenyu Zhang, Shengyuan Chen, Tianlong Chen, Xiao Huang, Zhangyang Wang, Xia Hu:
QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks. CoRR abs/2211.07379 (2022) - [i79]Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu:
Mitigating Relational Bias on Knowledge Graphs. CoRR abs/2211.14489 (2022) - [i78]Huiyuan Chen, Xiaoting Li, Kaixiong Zhou, Xia Hu, Chin-Chia Michael Yeh, Yan Zheng, Hao Yang:
TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems. CoRR abs/2212.04540 (2022) - [i77]Cameron Diao, Kaixiong Zhou, Xiao Huang, Xia Hu:
MolCPT: Molecule Continuous Prompt Tuning to Generalize Molecular Representation Learning. CoRR abs/2212.10614 (2022) - [i76]Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection. CoRR abs/2212.12488 (2022) - [i75]Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi:
Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising. CoRR abs/2212.12533 (2022) - 2021
- [j30]Mengnan Du, Fan Yang, Na Zou, Xia Hu:
Fairness in Deep Learning: A Computational Perspective. IEEE Intell. Syst. 36(4): 25-34 (2021) - [j29]Imtiaz Ahmed, Xia Ben Hu, Mithun P. Acharya, Yu Ding:
Neighborhood Structure Assisted Non-negative Matrix Factorization and Its Application in Unsupervised Point-wise Anomaly Detection. J. Mach. Learn. Res. 22: 34:1-34:32 (2021) - [j28]Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning credible DNNs via incorporating prior knowledge and model local explanation. Knowl. Inf. Syst. 63(2): 305-332 (2021) - [j27]Fan Yang, Ninghao Liu, Mengnan Du, Xia Hu:
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation. SIGKDD Explor. 23(1): 59-68 (2021) - [j26]Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu:
Adversarial Attacks and Defenses: An Interpretation Perspective. SIGKDD Explor. 23(1): 86-99 (2021) - [c122]Qiaoyu Tan, Jianwei Zhang, Ninghao Liu, Xiao Huang, Hongxia Yang, Jingren Zhou, Xia Hu:
Dynamic Memory based Attention Network for Sequential Recommendation. AAAI 2021: 4384-4392 - [c121]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu:
A Unified Taylor Framework for Revisiting Attribution Methods. AAAI 2021: 11462-11469 - [c120]Kwei-Herng Lai, Daochen Zha, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Minyang Wan, Diego Martinez, Xia Ben Hu:
TODS: An Automated Time Series Outlier Detection System. AAAI 2021: 16060-16062 - [c119]Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu:
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization. ICCV 2021: 4742-4750 - [c118]Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu:
AutoOD: Neural Architecture Search for Outlier Detection. ICDE 2021: 2117-2122 - [c117]Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu:
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments. ICLR 2021 - [c116]Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu:
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning. ICML 2021: 12333-12344 - [c115]Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan:
Machine Learning Explanations to Prevent Overtrust in Fake News Detection. ICWSM 2021: 421-431 - [c114]Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. KDD 2021: 258-268 - [c113]Fan Yang, Sahan Suresh Alva, Jiahao Chen, Xia Hu:
Model-Based Counterfactual Synthesizer for Interpretation. KDD 2021: 1964-1974 - [c112]Mengnan Du, Varun Manjunatha, Rajiv Jain, Ruchi Deshpande, Franck Dernoncourt, Jiuxiang Gu, Tong Sun, Xia Hu:
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models. NAACL-HLT 2021: 915-929 - [c111]Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Hassan Awadallah, Xia Ben Hu:
Fairness via Representation Neutralization. NeurIPS 2021: 12091-12103 - [c110]Kwei-Herng Lai, Daochen Zha, Junjie Xu, Yue Zhao, Guanchu Wang, Xia Ben Hu:
Revisiting Time Series Outlier Detection: Definitions and Benchmarks. NeurIPS Datasets and Benchmarks 2021 - [c109]Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. NeurIPS 2021: 21834-21846 - [c108]Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao, Ninghao Liu, Jingren Zhou, Hongxia Yang, Xia Hu:
Sparse-Interest Network for Sequential Recommendation. WSDM 2021: 598-606 - [c107]Ruixiang Tang, Mengnan Du, Yuening Li, Zirui Liu, Na Zou, Xia Hu:
Mitigating Gender Bias in Captioning Systems. WWW 2021: 633-645 - [i74]Fan Yang, Ninghao Liu, Mengnan Du, Xia Hu:
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation. CoRR abs/2101.06930 (2021) - [i73]Daochen Zha, Wenye Ma, Lei Yuan, Xia Hu, Ji Liu:
Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments. CoRR abs/2101.08152 (2021) - [i72]Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao, Ninghao Liu, Jingren Zhou, Hongxia Yang, Xia Hu:
Sparse-Interest Network for Sequential Recommendation. CoRR abs/2102.09267 (2021) - [i71]Qiaoyu Tan, Jianwei Zhang, Ninghao Liu, Xiao Huang, Hongxia Yang, Jingren Zhou, Xia Hu:
Dynamic Memory based Attention Network for Sequential Recommendation. CoRR abs/2102.09269 (2021) - [i70]Mengnan Du, Varun Manjunatha, Rajiv Jain, Ruchi Deshpande, Franck Dernoncourt, Jiuxiang Gu, Tong Sun, Xia Hu:
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models. CoRR abs/2103.06922 (2021) - [i69]Raj Vardhan, Ninghao Liu, Phakpoom Chinprutthiwong, Weijie Fu, Zhenyu Hu, Xia Ben Hu, Guofei Gu:
ExAD: An Ensemble Approach for Explanation-based Adversarial Detection. CoRR abs/2103.11526 (2021) - [i68]Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu:
DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization. CoRR abs/2103.14545 (2021) - [i67]Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. CoRR abs/2104.06629 (2021) - [i66]Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Denghui Zhang, Haifeng Chen, Xia Hu:
Learning Disentangled Representations for Time Series. CoRR abs/2105.08179 (2021) - [i65]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Simplifying Deep Reinforcement Learning via Self-Supervision. CoRR abs/2106.05526 (2021) - [i64]Daochen Zha, Jingru Xie, Wenye Ma, Sheng Zhang, Xiangru Lian, Xia Hu, Ji Liu:
DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning. CoRR abs/2106.06135 (2021) - [i63]Fan Yang, Sahan Suresh Alva, Jiahao Chen, Xia Hu:
Model-Based Counterfactual Synthesizer for Interpretation. CoRR abs/2106.08971 (2021) - [i62]Mengnan Du, Subhabrata Mukherjee, Guanchu Wang, Ruixiang Tang, Ahmed Hassan Awadallah, Xia Ben Hu:
Fairness via Representation Neutralization. CoRR abs/2106.12674 (2021) - [i61]Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Dirichlet Energy Constrained Learning for Deep Graph Neural Networks. CoRR abs/2107.02392 (2021) - [i60]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, Xia Hu:
AutoVideo: An Automated Video Action Recognition System. CoRR abs/2108.04212 (2021) - [i59]Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang:
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. CoRR abs/2108.10521 (2021) - [i58]Kaixiong Zhou, Ninghao Liu, Fan Yang, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu:
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. CoRR abs/2108.13555 (2021) - [i57]Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang:
Orthogonal Graph Neural Networks. CoRR abs/2109.11338 (2021) - [i56]Mengnan Du, Subhabrata Mukherjee, Yu Cheng, Milad Shokouhi, Xia Hu, Ahmed Hassan Awadallah:
What do Compressed Large Language Models Forget? Robustness Challenges in Model Compression. CoRR abs/2110.08419 (2021) - [i55]Haotian Xue, Kaixiong Zhou, Tianlong Chen, Kai Guo, Xia Hu, Yi Chang, Xin Wang:
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks. CoRR abs/2110.14855 (2021) - [i54]Ruixiang Tang, Ninghao Liu, Fan Yang, Na Zou, Xia Hu:
Defense Against Explanation Manipulation. CoRR abs/2111.04303 (2021) - 2020
- [j25]Yang Yang, Cheng Zhang, Chao Fan, Ali Mostafavi, Xia Hu:
Towards Fairness-Aware Disaster Informatics: an Interdisciplinary Perspective. IEEE Access 8: 201040-201054 (2020) - [j24]Chao Fan, Jiayi Shen, Ali Mostafavi, Xia Hu:
Characterizing reticulation in online social networks during disasters. Appl. Netw. Sci. 5(1): 29 (2020) - [j23]Mengnan Du, Ninghao Liu, Xia Hu:
Techniques for interpretable machine learning. Commun. ACM 63(1): 68-77 (2020) - [j22]Bin Guo, Xing Xie, Lina Yao, Yong Li, Xia Hu:
Correction to: Special issue on recommender system. CCF Trans. Pervasive Comput. Interact. 2(1): 78 (2020) - [j21]Yi-Wei Chen, Qingquan Song, Xi Liu, P. S. Sastry, Xia Hu:
On Robustness of Neural Architecture Search Under Label Noise. Frontiers Big Data 3: 2 (2020) - [j20]Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu:
A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter. BMC Medical Informatics Decis. Mak. 20-S(4): 254 (2020) - [j19]Yi-Wei Chen, Qingquan Song, Xia Hu:
Techniques for Automated Machine Learning. SIGKDD Explor. 22(2): 35-50 (2020) - [c106]Yan Zhong, Xiao Huang, Jundong Li, Xia Hu:
Scalable Social Tie Strength Measuring. ASONAM 2020: 288-295 - [c105]Mengnan Du, Shiva K. Pentyala, Yuening Li, Xia Hu:
Towards Generalizable Deepfake Detection with Locality-aware AutoEncoder. CIKM 2020: 325-334 - [c104]Ninghao Liu, Yong Ge, Li Li, Xia Hu, Rui Chen, Soo-Hyun Choi:
Explainable Recommender Systems via Resolving Learning Representations. CIKM 2020: 895-904 - [c103]Haofan Wang, Zifan Wang, Mengnan Du, Fan Yang, Zijian Zhang, Sirui Ding, Piotr Mardziel, Xia Hu:
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks. CVPR Workshops 2020: 111-119 - [c102]Daochen Zha, Kwei-Herng Lai, Mingyang Wan, Xia Hu:
Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning. ICDM 2020: 771-780 - [c101]Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu:
Multi-Channel Graph Neural Networks. IJCAI 2020: 1352-1358 - [c100]Kwei-Herng Lai, Daochen Zha, Yuening Li, Xia Hu:
Dual Policy Distillation. IJCAI 2020: 3146-3152 - [c99]Daochen Zha, Kwei-Herng Lai, Songyi Huang, Yuanpu Cao, Keerthana Reddy, Juan Vargas, Alex Nguyen, Ruzhe Wei, Junyu Guo, Xia Hu:
RLCard: A Platform for Reinforcement Learning in Card Games. IJCAI 2020: 5264-5266 - [c98]Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks. KDD 2020: 218-228 - [c97]Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji:
XGNN: Towards Model-Level Explanations of Graph Neural Networks. KDD 2020: 430-438 - [c96]Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu:
Policy-GNN: Aggregation Optimization for Graph Neural Networks. KDD 2020: 461-471 - [c95]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. KDD 2020: 945-955 - [c94]Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu:
Detecting Interactions from Neural Networks via Topological Analysis. NeurIPS 2020 - [c93]Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu:
Towards Deeper Graph Neural Networks with Differentiable Group Normalization. NeurIPS 2020 - [c92]Ting-Hsiang Wang, Xia Hu, Haifeng Jin, Qingquan Song, Xiaotian Han, Zirui Liu:
AutoRec: An Automated Recommender System. RecSys 2020: 582-584 - [c91]Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu:
Deep Neural Networks with Knowledge Instillation. SDM 2020: 370-378 - [c90]Yuening Li, Daochen Zha, Praveen Kumar Venugopal, Na Zou, Xia Hu:
PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning. WWW (Companion Volume) 2020: 153-157 - [c89]Qiaoyu Tan, Ninghao Liu, Xing Zhao, Hongxia Yang, Jingren Zhou, Xia Hu:
Learning to Hash with Graph Neural Networks for Recommender Systems. WWW 2020: 1988-1998 - [e1]James Caverlee, Xia (Ben) Hu, Mounia Lalmas, Wei Wang:
WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020. ACM 2020, ISBN 978-1-4503-6822-3 [contents] - [i53]Imtiaz Ahmed, Xia Ben Hu, Mithun P. Acharya, Yu Ding:
Neighborhood Structure Assisted Non-negative Matrix Factorization and its Application in Unsupervised Point Anomaly Detection. CoRR abs/2001.06541 (2020) - [i52]Qiaoyu Tan, Ninghao Liu, Xing Zhao, Hongxia Yang, Jingren Zhou, Xia Hu:
Learning to Hash with Graph Neural Networks for Recommender Systems. CoRR abs/2003.01917 (2020) - [i51]Yuening Li, Daochen Zha, Praveen Kumar Venugopal, Na Zou, Xia Hu:
PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning. CoRR abs/2003.05602 (2020) - [i50]Ninghao Liu, Mengnan Du, Xia Hu:
Adversarial Machine Learning: An Interpretation Perspective. CoRR abs/2004.11488 (2020) - [i49]Zhengyang Wang, Xia Hu, Shuiwang Ji:
iCapsNets: Towards Interpretable Capsule Networks for Text Classification. CoRR abs/2006.00075 (2020) - [i48]Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji:
XGNN: Towards Model-Level Explanations of Graph Neural Networks. CoRR abs/2006.02587 (2020) - [i47]Kwei-Herng Lai, Daochen Zha, Yuening Li, Xia Hu:
Dual Policy Distillation. CoRR abs/2006.04061 (2020) - [i46]Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu:
Towards Deeper Graph Neural Networks with Differentiable Group Normalization. CoRR abs/2006.06972 (2020) - [i45]Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks. CoRR abs/2006.08131 (2020) - [i44]Ruixiang Tang, Mengnan Du, Yuening Li, Zirui Liu, Xia Hu:
Mitigating Gender Bias in Captioning Systems. CoRR abs/2006.08315 (2020) - [i43]Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, Xia Hu:
AutoOD: Automated Outlier Detection via Curiosity-guided Search and Self-imitation Learning. CoRR abs/2006.11321 (2020) - [i42]Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu:
Policy-GNN: Aggregation Optimization for Graph Neural Networks. CoRR abs/2006.15097 (2020) - [i41]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. CoRR abs/2007.06434 (2020) - [i40]Ting-Hsiang Wang, Qingquan Song, Xiaotian Han, Zirui Liu, Haifeng Jin, Xia Hu:
AutoRec: An Automated Recommender System. CoRR abs/2007.07224 (2020) - [i39]Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan:
Machine Learning Explanations to Prevent Overtrust in Fake News Detection. CoRR abs/2007.12358 (2020) - [i38]Ninghao Liu, Yong Ge, Li Li, Xia Hu, Rui Chen, Soo-Hyun Choi:
Explainable Recommender Systems via Resolving Learning Representations. CoRR abs/2008.09316 (2020) - [i37]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu:
A Unified Taylor Framework for Revisiting Attribution Methods. CoRR abs/2008.09695 (2020) - [i36]Daochen Zha, Kwei-Herng Lai, Mingyang Wan, Xia Hu:
Meta-AAD: Active Anomaly Detection with Deep Reinforcement Learning. CoRR abs/2009.07415 (2020) - [i35]Ninghao Liu, Yunsong Meng, Xia Hu, Tie Wang, Bo Long:
Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability. CoRR abs/2009.07494 (2020) - [i34]Kwei-Herng Lai, Daochen Zha, Guanchu Wang, Junjie Xu, Yue Zhao, Devesh Kumar, Yile Chen, Purav Zumkhawaka, Minyang Wan, Diego Martinez, Xia Ben Hu:
TODS: An Automated Time Series Outlier Detection System. CoRR abs/2009.09822 (2020) - [i33]Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu:
Towards Interaction Detection Using Topological Analysis on Neural Networks. CoRR abs/2010.13015 (2020) - [i32]Imtiaz Ahmed, Travis Galoppo, Xia Ben Hu, Yu Ding:
Graph Regularized Autoencoder and its Application in Unsupervised Anomaly Detection. CoRR abs/2010.15949 (2020) - [i31]Ruixiang Tang, Mengnan Du, Xia Hu:
Deep Serial Number: Computational Watermarking for DNN Intellectual Property Protection. CoRR abs/2011.08960 (2020)
2010 – 2019
- 2019
- [j18]Hao Yuan, Lei Cai, Zhengyang Wang, Xia Hu, Shaoting Zhang, Shuiwang Ji:
Computational modeling of cellular structures using conditional deep generative networks. Bioinform. 35(12): 2141-2149 (2019) - [j17]Bin Guo, Xing Xie, Lina Yao, Yong Li, Cecilia Mascolo, Xia Hu:
Special issue on recommender system. CCF Trans. Pervasive Comput. Interact. 1(4): 237-239 (2019) - [j16]Qiaoyu Tan, Ninghao Liu, Xia Hu:
Deep Representation Learning for Social Network Analysis. Frontiers Big Data 2: 2 (2019) - [j15]Cheng Zhang, Chao Fan, Wenlin Yao, Xia Hu, Ali Mostafavi:
Social media for intelligent public information and warning in disasters: An interdisciplinary review. Int. J. Inf. Manag. 49: 190-207 (2019) - [j14]Qingquan Song, Hancheng Ge, James Caverlee, Xia Hu:
Tensor Completion Algorithms in Big Data Analytics. ACM Trans. Knowl. Discov. Data 13(1): 6:1-6:48 (2019) - [c88]Jiaxu Cui, Bo Yang, Xia Hu:
Deep Bayesian Optimization on Attributed Graphs. AAAI 2019: 1377-1384 - [c87]Xiao Huang, Qingquan Song, Fan Yang, Xia Hu:
Large-Scale Heterogeneous Feature Embedding. AAAI 2019: 3878-3885 - [c86]Hao Yuan, Yongjun Chen, Xia Hu, Shuiwang Ji:
Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods. AAAI 2019: 5717-5724 - [c85]Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning Credible Deep Neural Networks with Rationale Regularization. ICDM 2019: 150-159 - [c84]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Experience Replay Optimization. IJCAI 2019: 4243-4249 - [c83]Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu:
Deep Structured Cross-Modal Anomaly Detection. IJCNN 2019: 1-8 - [c82]Qingquan Song, Shiyu Chang, Xia Hu:
Coupled Variational Recurrent Collaborative Filtering. KDD 2019: 335-343 - [c81]Xiao Huang, Qingquan Song, Yuening Li, Xia Hu:
Graph Recurrent Networks With Attributed Random Walks. KDD 2019: 732-740 - [c80]Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, Xia Hu:
Is a Single Vector Enough?: Exploring Node Polysemy for Network Embedding. KDD 2019: 932-940 - [c79]Haifeng Jin, Qingquan Song, Xia Hu:
Auto-Keras: An Efficient Neural Architecture Search System. KDD 2019: 1946-1956 - [c78]Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu:
Identification of Cancer Survivors Living with PTSD on Social Media. MedInfo 2019: 1468-1469 - [c77]Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu:
An Interpretable Neural Model with Interactive Stepwise Influence. PAKDD (3) 2019: 528-540 - [c76]Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu:
Using Deep Neural Network to Identify Cancer Survivors Living with Post-Traumatic Stress Disorder on Social Media. SEPDA@ISWC 2019: 48-52 - [c75]Ninghao Liu, Mengnan Du, Xia Hu:
Representation Interpretation with Spatial Encoding and Multimodal Analytics. WSDM 2019: 60-68 - [c74]Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu:
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. WWW 2019: 383-393 - [c73]Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu:
XFake: Explainable Fake News Detector with Visualizations. WWW 2019: 3600-3604 - [i30]Qingquan Song, Haifeng Jin, Xiao Huang, Xia Hu:
Multi-Label Adversarial Perturbations. CoRR abs/1901.00546 (2019) - [i29]Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu:
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. CoRR abs/1903.11245 (2019) - [i28]Sina Mohseni, Eric D. Ragan, Xia Hu:
Open Issues in Combating Fake News: Interpretability as an Opportunity. CoRR abs/1904.03016 (2019) - [i27]Qiaoyu Tan, Ninghao Liu, Xia Hu:
Deep Representation Learning for Social Network Analysis. CoRR abs/1904.08547 (2019) - [i26]Ninghao Liu, Qiaoyu Tan, Yuening Li, Hongxia Yang, Jingren Zhou, Xia Hu:
Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding. CoRR abs/1905.10668 (2019) - [i25]Jiaxu Cui, Bo Yang, Xia Hu:
Deep Bayesian Optimization on Attributed Graphs. CoRR abs/1905.13403 (2019) - [i24]Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu:
Experience Replay Optimization. CoRR abs/1906.08387 (2019) - [i23]Fan Yang, Mengnan Du, Xia Hu:
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning. CoRR abs/1907.06831 (2019) - [i22]Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu:
XFake: Explainable Fake News Detector with Visualizations. CoRR abs/1907.07757 (2019) - [i21]Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu:
Deep Structured Cross-Modal Anomaly Detection. CoRR abs/1908.03848 (2019) - [i20]Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
Learning Credible Deep Neural Networks with Rationale Regularization. CoRR abs/1908.05601 (2019) - [i19]Mengnan Du, Fan Yang, Na Zou, Xia Hu:
Fairness in Deep Learning: A Computational Perspective. CoRR abs/1908.08843 (2019) - [i18]Kaixiong Zhou, Qingquan Song, Xiao Huang, Xia Hu:
Auto-GNN: Neural Architecture Search of Graph Neural Networks. CoRR abs/1909.03184 (2019) - [i17]Mengnan Du, Shiva K. Pentyala, Yuening Li, Xia Hu:
Towards Generalizable Forgery Detection with Locality-aware AutoEncoder. CoRR abs/1909.05999 (2019) - [i16]Yijun Bian, Qingquan Song, Mengnan Du, Jun Yao, Huanhuan Chen, Xia Hu:
Sub-Architecture Ensemble Pruning in Neural Architecture Search. CoRR abs/1910.00370 (2019) - [i15]Zijian Zhang, Fan Yang, Haofan Wang, Xia Hu:
Contextual Local Explanation for Black Box Classifiers. CoRR abs/1910.00768 (2019) - [i14]Yuening Li, Daochen Zha, Na Zou, Xia Hu:
PyODDS: An End-to-End Outlier Detection System. CoRR abs/1910.02575 (2019) - [i13]Daochen Zha, Kwei-Herng Lai, Yuanpu Cao, Songyi Huang, Ruzhe Wei, Junyu Guo, Xia Hu:
RLCard: A Toolkit for Reinforcement Learning in Card Games. CoRR abs/1910.04376 (2019) - [i12]Fan Yang, Zijian Zhang, Haofan Wang, Yuening Li, Xia Hu:
XDeep: An Interpretation Tool for Deep Neural Networks. CoRR abs/1911.01005 (2019) - [i11]Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu:
Multi-Channel Graph Convolutional Networks. CoRR abs/1912.08306 (2019) - 2018
- [j13]Xia Hu, Gregor Stiglic, Fei Wang:
Special Issue on Data Mining in Health Informatics. J. Heal. Informatics Res. 2(4): 367-369 (2018) - [j12]Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu:
Understanding and Identifying Rhetorical Questions in Social Media. ACM Trans. Intell. Syst. Technol. 9(2): 17:1-17:22 (2018) - [j11]Xiao Huang, Jundong Li, Na Zou, Xia Hu:
A General Embedding Framework for Heterogeneous Information Learning in Large-Scale Networks. ACM Trans. Knowl. Discov. Data 12(6): 70:1-70:24 (2018) - [c72]Zepeng Huo, Xiao Huang, Xia Hu:
Link Prediction With Personalized Social Influence. AAAI 2018: 2289-2296 - [c71]Ziwei Zhu, Xia Hu, James Caverlee:
Fairness-Aware Tensor-Based Recommendation. CIKM 2018: 1153-1162 - [c70]Hancheng Ge, Kai Zhang, Majid Alfifi, Xia Hu, James Caverlee:
DisTenC: A Distributed Algorithm for Scalable Tensor Completion on Spark. ICDE 2018: 137-148 - [c69]Fan Yang, Ninghao Liu, Suhang Wang, Xia Hu:
Towards Interpretation of Recommender Systems with Sorted Explanation Paths. ICDM 2018: 667-676 - [c68]Qingquan Song, Haifeng Jin, Xiao Huang, Xia Hu:
Multi-label Adversarial Perturbations. ICDM 2018: 1242-1247 - [c67]Ninghao Liu, Donghwa Shin, Xia Hu:
Contextual Outlier Interpretation. IJCAI 2018: 2461-2467 - [c66]Jinxue Zhang, Jingchao Sun, Rui Zhang, Yanchao Zhang, Xia Hu:
Privacy-Preserving Social Media Data Outsourcing. INFOCOM 2018: 1106-1114 - [c65]Mengnan Du, Ninghao Liu, Qingquan Song, Xia Hu:
Towards Explanation of DNN-based Prediction with Guided Feature Inversion. KDD 2018: 1358-1367 - [c64]Ninghao Liu, Hongxia Yang, Xia Hu:
Adversarial Detection with Model Interpretation. KDD 2018: 1803-1811 - [c63]Ninghao Liu, Xiao Huang, Jundong Li, Xia Hu:
On Interpretation of Network Embedding via Taxonomy Induction. KDD 2018: 1812-1820 - [c62]Xing Zhao, Qingquan Song, James Caverlee, Xia Hu:
TrailMix: An Ensemble Recommender System for Playlist Curation and Continuation. RecSys Challenge 2018: 8:1-8:6 - [c61]Xiao Huang, Qingquan Song, Jundong Li, Xia Hu:
Exploring Expert Cognition for Attributed Network Embedding. WSDM 2018: 270-278 - [r1]Ninghao Liu, Xia Hu:
Spam Detection on Social Networks. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i10]Mengnan Du, Ninghao Liu, Qingquan Song, Xia Hu:
Towards Explanation of DNN-based Prediction with Guided Feature Inversion. CoRR abs/1804.00506 (2018) - [i9]Yang Yang, Xia Hu, Haoyan Liu, Jiawei Zhang, Zhoujun Li, Philip S. Yu:
Understanding and Monitoring Human Trafficking via Social Sensors: A Sociological Approach. CoRR abs/1805.10617 (2018) - [i8]Yang Yang, Xia Hu, Haoyan Liu, Jiawei Zhang, Zhoujun Li, Philip S. Yu:
r-instance Learning for Missing People Tweets Identification. CoRR abs/1805.10856 (2018) - [i7]Mengnan Du, Ninghao Liu, Xia Hu:
Techniques for Interpretable Machine Learning. CoRR abs/1808.00033 (2018) - 2017
- [j10]Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu:
Facilitating Time Critical Information Seeking in Social Media. IEEE Trans. Knowl. Data Eng. 29(10): 2197-2209 (2017) - [j9]Mohammad Akbari, Xia Hu, Fei Wang, Tat-Seng Chua:
Wellness Representation of Users in Social Media: Towards Joint Modelling of Heterogeneity and Temporality. IEEE Trans. Knowl. Data Eng. 29(10): 2360-2373 (2017) - [j8]Da Cao, Xiangnan He, Liqiang Nie, Xiaochi Wei, Xia Hu, Shunxiang Wu, Tat-Seng Chua:
Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts. ACM Trans. Inf. Syst. 35(4): 37:1-37:27 (2017) - [c60]Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu:
Attributed Network Embedding for Learning in a Dynamic Environment. CIKM 2017: 387-396 - [c59]Xia Hu, Shuiwang Ji:
IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models. CIKM 2017: 2565-2566 - [c58]Liang Wu, Xia Hu, Fred Morstatter, Huan Liu:
Adaptive Spammer Detection with Sparse Group Modeling. ICWSM 2017: 319-326 - [c57]Liang Wu, Xia Hu, Huan Liu:
Early Identification of Personalized Trending Topics in Microblogging. ICWSM 2017: 692-695 - [c56]Liang Wu, Xia Hu, Fred Morstatter, Huan Liu:
Detecting Camouflaged Content Polluters. ICWSM 2017: 696-699 - [c55]Jundong Li, Harsh Dani, Xia Hu, Huan Liu:
Radar: Residual Analysis for Anomaly Detection in Attributed Networks. IJCAI 2017: 2152-2158 - [c54]Ninghao Liu, Xiao Huang, Xia Hu:
Accelerated Local Anomaly Detection via Resolving Attributed Networks. IJCAI 2017: 2337-2343 - [c53]Qingquan Song, Xiao Huang, Hancheng Ge, James Caverlee, Xia Hu:
Multi-Aspect Streaming Tensor Completion. KDD 2017: 435-443 - [c52]Liang Wu, Jundong Li, Xia Hu, Huan Liu:
Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media. SDM 2017: 99-107 - [c51]Xiao Huang, Jundong Li, Xia Hu:
Accelerated Attributed Network Embedding. SDM 2017: 633-641 - [c50]Cheng Cao, Hancheng Ge, Haokai Lu, Xia Hu, James Caverlee:
What Are You Known For?: Learning User Topical Profiles with Implicit and Explicit Footprints. SIGIR 2017: 743-752 - [c49]