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ORCIDYan Liu 0002
Person information
- affiliation: University of Southern California, Computer Science Department, Los Angeles, CA, USA
- affiliation (former): IBM T. J. Watson Research Center, CA, USA
- affiliation (former): Carnegie Mellon University, Language Technologies Institute, Pittsburgh, PA, USA
Other persons with the same name
- Yan Liu — disambiguation page
- Yan Liu 0001
![[0000-0002-6747-8151]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-6747-8151")
— Concordia University, Montreal, PQ, Canada (and 3 more) - Yan Liu 0003 — Motorala Labs
- Yan Liu 0004 (aka: Fiona Yan Liu) — Hong Kong Polytechnic University, Department of Computing, Cognitive Computing Lab, Hong Kong (and 1 more)
- Yan Liu 0005 — University of Ottawa, Canada
- Yan Liu 0006 — Information Engineering University, Information Engineering Institute, Zhengzhou, China
- Yan Liu 0007 — Beijing Normal University, China
- Yan Liu 0008 — Wright State University, Department of Biomedical, Industrial, and Human Factors Engineering, Dayton, OH, USA
- Yan Liu 0009 (aka: Yan Y. Liu) — University of Illinois at Urbana-Champaign, IL, USA
- Yan Liu 0010 — Huazhong University, School of Computer Science and Technology, Key Laboratory of Data Storage System, China
- Yan Liu 0011 — Tongji University, Shanghai, China
- Yan Liu 0012 — Ant Financial, Hangzhou, China (and 1 more)
- Yan Liu 0013 — University of Queensland, School of Earth Sciences, Centre for Geoscience Computing
- Yan Liu 0014 — Harbin Institute of Technology, Department of Mathematics, China
- Yan Liu 0015 — Dalian Polytechnic University, School of Information Science and Engineering, China (and 1 more)
- Yan Liu 0016 — Shanghai JiaoTong University, Bio-Circuits and Systems Laboratory, China (and 1 more)
- Yan Liu 0017 — Xerox Research Centre Euorpe (and 1 more)
- Yan Liu 0018 — Hangzhou Dianzi University, School of Electronics and Information, China (and 1 more)
- Yan Liu 0019 — Guandong University of Finance
- Yan Liu 0020 — Beijing Institute of Technology, State Key Laboratory of Explosion Science and Technology, Beijing, China
- Yan Liu 0021 — Peking University, School of Software and Microelectronics, Beijing, China
- Yan Liu 0022 — Stony Brook University, Department of Radiology, NY, USA
- Yan Liu 0024 — Siemens (and 2 more)
- Yan Liu 0025 — Texas A & M University
- Yan Liu 0026 — Delft University of Technology, Faculty of Civil Engineering and Geosciences, Delft, Netherlands (and 1 more)
- Yan Liu 0027 — University of Science and Technology of China, School of Management, China
- Yan Liu 0028 — Harbin University of Science and Technology, Department of Automation, China
- Yan Liu 0029 — University of Michigan, Department of Naval Architecture and Marine Engineering, Ann Arbor, MI, USA
- Yan Liu 0030 — South China Normal University, School of Mathematical Sciences, Guangzhou, China
- Yan Liu 0031 — Tsinghua University, Department of Electronic Engineering, Beijing, China
- Yan Liu 0032 — Hunan University, College of Computer Science and Electronic Engineering, Changsha, China
- Yan Liu 0033 — Waseda University, Department of Applied Mathematics, Okubo, Japan
- Yan Liu 0034 — Northwestern Polytechnical University, School of Aeronautics, Xi'an, China
- Yan Liu 0035 — Inner Mongolia Agricultural University, College of Economics and Management, Hohhot, China
- Yan Liu 0036 — University of Warwick, Coventry, UK
- Yan Liu 0037 — Arizona State University, Tempe, AZ, USA
- Yan Liu 0038 — Yangzhou University, School of Information Engineering, Yangzhou, China
- Yan Liu 0039 — Changchun University of Science and Technology, School of Computer Science and Technology, Changchun, China (and 1 more)
- Yan Liu 0040 — Tianjin University, College of Management and Economics, Tianjin, China
- Yan Liu 0041 — Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Department of Medical Image, China (and 2 more)
- Yan Liu 0042 — Guangdong Polytechnic Normal University, School of Electronic and Information, Guangzhou, China
- Yan Liu 0043 — Sichuan University, College of Electronics and Information Engineering, Chengdu, China
- Yan Liu 0044 — North China Electric Power University, Department of Economics and Management, Baoding, China (and 1 more)
- Yan Liu 0045 — Peking University, School of Computer Science, Beijing, China (and 1 more)
- Yan Liu 0046 — Anhui University, School of Mathematical Sciences, Hefei, China
- Yan Liu 0047 — University of Electronic Science and Technology of China, Chengdu, China (and 1 more)
- Yan Liu 0048 — Jiangsu Academy of Agricultural Sciences, Nanjing, China
- Yan Liu 0049 — Xidian University, School of Electro-Mechanical Engineering, Key Laboratory of Electronic Equipment Structure Design, Xi'an, China (and 1 more)
- Yan Liu 0050 — Shanghai Jiaotong University, Department of Mathematics, Shanghai, China
- Yan Liu 0051 — Hebei University, College of Cyberspace Security and Computer, Baoding, China
- Yan Liu 0052 — Sichuan University, College of Electrical Engineering, China
- Yan Liu 0053 — Nanjing University of Information Science and Technology, School of Automation, China (and 1 more)
Other persons with a similar name
- Dayan Liu (aka: Da-Yan Liu)
- Keyan Liu (aka: Ke-yan Liu, Ke-Yan Liu)
- Tie-Yan Liu — Microsoft Research Asia, Beijing, China
- Xiaoyan Liu (aka: Xiao-yan Liu, Xiao-Yan Liu) — disambiguation page
- Yanjun Liu (aka: Yan-Jun Liu, Yan-jun Liu, Yan Jun Liu) — disambiguation page
- Yanping Liu (aka: Yan-Ping Liu) — disambiguation page
- Yian-Kui Liu (aka: Yan-Kui Liu, Yankui Liu) — Hebei University, College of Mathematics and Computer Science, Baoding, China
- Ziyan Liu (aka: Zi-Yan Liu, Zi Yan Liu) — disambiguation page
- Yan-Xiao Liu 0001 (aka: Yanxiao Liu 0001) — Xi'an University of Technology, Department of Computer Science and Engineering, China (and 1 more)
- Yan-Jun Liu 0003 (aka: Yanjun Liu 0003) — Liaoning University of Technology, College of Science, Jinzhou, China (and 2 more)
- show all similar names
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2020 – today
- 2024
[c151]Furong Jia, Kevin Wang, Yixiang Zheng, Defu Cao, Yan Liu:
GPT4MTS: Prompt-based Large Language Model for Multimodal Time-series Forecasting. AAAI 2024: 23343-23351- [c150]Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Wei Shen, Limao Xiong, Yuhao Zhou, Xiao Wang, Zhiheng Xi, Xiaoran Fan, Shiliang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang:
LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin. ACL (1) 2024: 1932-1945 - [c149]Shihan Dou, Yan Liu, Haoxiang Jia, Enyu Zhou, Limao Xiong, Junjie Shan, Caishuang Huang, Xiao Wang, Xiaoran Fan, Zhiheng Xi, Yuhao Zhou, Tao Ji, Rui Zheng, Qi Zhang, Tao Gui, Xuanjing Huang:
StepCoder: Improving Code Generation with Reinforcement Learning from Compiler Feedback. ACL (1) 2024: 4571-4585 - [c148]James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister:
TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents. ACL (Findings) 2024: 13984-14011 - [c147]Shitong Duan, Xiaoyuan Yi, Peng Zhang, Yan Liu, Zheng Liu, Tun Lu, Xing Xie, Ning Gu:
Negating Negatives: Alignment with Human Negative Samples via Distributional Dispreference Optimization. EMNLP (Findings) 2024: 1012-1042 - [c146]Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu:
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. ICLR 2024 - [c145]Yan Liu, Yu Liu, Xiaokang Chen, Pin-Yu Chen, Daoguang Zan, Min-Yen Kan, Tsung-Yi Ho:
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models. ICLR 2024 - [c144]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c143]Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang, Yan Liu:
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series. ICML 2024 - [c142]Yizhou Zhang, Karishma Sharma, Lun Du, Yan Liu:
Toward Mitigating Misinformation and Social Media Manipulation in LLM Era. WWW (Companion Volume) 2024: 1302-1305 - [i79]Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John C. Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i78]Binghai Wang, Rui Zheng, Lu Chen, Yan Liu, Shihan Dou, Caishuang Huang, Wei Shen, Senjie Jin, Enyu Zhou, Chenyu Shi, Songyang Gao, Nuo Xu, Yuhao Zhou, Xiaoran Fan, Zhiheng Xi, Jun Zhao, Xiao Wang, Tao Ji, Hang Yan, Lixing Shen, Zhan Chen, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Zuxuan Wu, Yu-Gang Jiang:
Secrets of RLHF in Large Language Models Part II: Reward Modeling. CoRR abs/2401.06080 (2024) - [i77]Shihan Dou, Yan Liu, Haoxiang Jia, Limao Xiong, Enyu Zhou, Wei Shen, Junjie Shan, Caishuang Huang, Xiao Wang, Xiaoran Fan, Zhiheng Xi, Yuhao Zhou, Tao Ji, Rui Zheng, Qi Zhang, Xuanjing Huang, Tao Gui:
StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback. CoRR abs/2402.01391 (2024) - [i76]Yizhou Zhang, Lun Du, Defu Cao, Qiang Fu, Yan Liu:
Prompting Large Language Models with Divide-and-Conquer Program for Discerning Problem Solving. CoRR abs/2402.05359 (2024) - [i75]Shihan Dou, Yan Liu, Enyu Zhou, Tianlong Li, Haoxiang Jia, Limao Xiong, Xin Zhao, Junjie Ye, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang:
MetaRM: Shifted Distributions Alignment via Meta-Learning. CoRR abs/2405.00438 (2024) - [i74]Yan Liu, Yu Liu, Xiaokang Chen, Pin-Yu Chen, Daoguang Zan, Min-Yen Kan, Tsung-Yi Ho:
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Pre-trained Language Models. CoRR abs/2406.10130 (2024) - [i73]Shihan Dou, Haoxiang Jia, Shenxi Wu, Huiyuan Zheng, Weikang Zhou, Muling Wu, Mingxu Chai, Jessica Fan, Caishuang Huang, Yunbo Tao, Yan Liu, Enyu Zhou, Ming Zhang, Yuhao Zhou, Yueming Wu, Rui Zheng, Ming Wen, Rongxiang Weng, Jingang Wang, Xunliang Cai, Tao Gui, Xipeng Qiu, Qi Zhang, Xuanjing Huang:
What's Wrong with Your Code Generated by Large Language Models? An Extensive Study. CoRR abs/2407.06153 (2024) - [i72]Can Rong, Jingtao Ding, Yan Liu, Yong Li:
A Large-scale Benchmark Dataset for Commuting Origin-destination Matrix Generation. CoRR abs/2407.15823 (2024) - [i71]Qiang Huang, Chuizheng Meng, Defu Cao, Biwei Huang, Yi Chang, Yan Liu:
An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series. CoRR abs/2408.08815 (2024) - [i70]Defu Cao, Wen Ye, Yizhou Zhang, Yan Liu:
TimeDiT: General-purpose Diffusion Transformers for Time Series Foundation Model. CoRR abs/2409.02322 (2024) - [i69]Yujia Zhou, Yan Liu, Xiaoxi Li, Jiajie Jin, Hongjin Qian, Zheng Liu, Chaozhuo Li, Zhicheng Dou, Tsung-Yi Ho, Philip S. Yu:
Trustworthiness in Retrieval-Augmented Generation Systems: A Survey. CoRR abs/2409.10102 (2024) - [i68]Yan Liu, Xiaoyuan Yi, Xiaokang Chen, Jing Yao, Jingwei Yi, Daoguang Zan, Zheng Liu, Xing Xie, Tsung-Yi Ho:
Elephant in the Room: Unveiling the Impact of Reward Model Quality in Alignment. CoRR abs/2409.19024 (2024) - [i67]Wen Ye, Yizhou Zhang, Wei Yang, Lumingyuan Tang, Defu Cao, Jie Cai, Yan Liu:
Beyond Forecasting: Compositional Time Series Reasoning for End-to-End Task Execution. CoRR abs/2410.04047 (2024) - 2023
- [c141]Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu:
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders. AAAI 2023: 6897-6905 - [c140]Songyang Gao, Shihan Dou, Yan Liu, Xiao Wang, Qi Zhang, Zhongyu Wei, Jin Ma, Ying Shan:
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization. ACL (1) 2023: 12177-12189 - [c139]Yan Liu, Yan Gao, Zhe Su, Xiaokang Chen, Elliott Ash, Jian-Guang Lou:
Uncovering and Categorizing Social Biases in Text-to-SQL. ACL (1) 2023: 13573-13584 - [c138]Defu Cao, Zhaowen Wang, Jose Echevarria, Yan Liu:
SVGformer: Representation Learning for Continuous Vector Graphics using Transformers. CVPR 2023: 10093-10102 - [c137]Yizhou Zhang, Karishma Sharma, Yan Liu:
Capturing Cross-Platform Interaction for Identifying Coordinated Accounts of Misinformation Campaigns. ECIR (2) 2023: 694-702 - [c136]Defu Cao, Yixiang Zheng, Parisa Hassanzadeh, Simran Lamba, Xiaomo Liu, Yan Liu:
Large Scale Financial Time Series Forecasting with Multi-faceted Model. ICAIF 2023: 472-480 - [c135]Loc Trinh, Tim Chu, Zijun Cui, Anand Malpani, Cherine Yang, Istabraq Dalieh, Alvin Hui, Oscar Gomez, Yan Liu, Andrew J. Hung:
Self-supervised Sim-to-Real Kinematics Reconstruction for Video-Based Assessment of Intraoperative Suturing Skills. MICCAI (9) 2023: 708-717 - [c134]Yan Liu, Xiaokang Chen, Yan Gao, Zhe Su, Fengji Zhang, Daoguang Zan, Jian-Guang Lou, Pin-Yu Chen, Tsung-Yi Ho:
Uncovering and Quantifying Social Biases in Code Generation. NeurIPS 2023 - [c133]Yizhou Zhang, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong, Haifeng Chen, Yan Liu:
Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning. NeurIPS 2023 - [c132]Hao Niu, Guillaume Habault, Roberto Legaspi, Chuizheng Meng, Defu Cao, Shinya Wada, Chihiro Ono, Yan Liu:
Time-delayed Multivariate Time Series Predictions. SDM 2023: 325-333 - [i66]Defu Cao, James Enouen, Yan Liu:
Estimating Treatment Effects in Continuous Time with Hidden Confounders. CoRR abs/2302.09446 (2023) - [i65]Defu Cao, James Enouen, Yujing Wang, Xiangchen Song, Chuizheng Meng, Hao Niu, Yan Liu:
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders. CoRR abs/2303.02320 (2023) - [i64]Yizhou Zhang, Loc Trinh, Defu Cao, Zijun Cui, Yan Liu:
Detecting Out-of-Context Multimodal Misinformation with interpretable neural-symbolic model. CoRR abs/2304.07633 (2023) - [i63]Yan Liu, Xiaokang Chen, Yan Gao, Zhe Su, Fengji Zhang, Daoguang Zan, Jian-Guang Lou, Pin-Yu Chen, Tsung-Yi Ho:
Uncovering and Quantifying Social Biases in Code Generation. CoRR abs/2305.15377 (2023) - [i62]Yan Liu, Yan Gao, Zhe Su, Xiaokang Chen, Elliott Ash, Jian-Guang Lou:
Uncovering and Categorizing Social Biases in Text-to-SQL. CoRR abs/2305.16253 (2023) - [i61]Songyang Gao, Shihan Dou, Yan Liu, Xiao Wang, Qi Zhang, Zhongyu Wei, Jin Ma, Ying Shan:
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization. CoRR abs/2306.15164 (2023) - [i60]Rui Zheng, Shihan Dou, Songyang Gao, Yuan Hua, Wei Shen, Binghai Wang, Yan Liu, Senjie Jin, Qin Liu, Yuhao Zhou, Limao Xiong, Lu Chen, Zhiheng Xi, Nuo Xu, Wenbin Lai, Minghao Zhu, Cheng Chang, Zhangyue Yin, Rongxiang Weng, Wensen Cheng, Haoran Huang, Tianxiang Sun, Hang Yan, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang:
Secrets of RLHF in Large Language Models Part I: PPO. CoRR abs/2307.04964 (2023) - [i59]James Enouen, Tianshu Sun, Yan Liu:
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments. CoRR abs/2309.01780 (2023) - [i58]Defu Cao, Furong Jia, Sercan Ö. Arik, Tomas Pfister, Yixiang Zheng, Wen Ye, Yan Liu:
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. CoRR abs/2310.04948 (2023) - [i57]Chuizheng Meng, Yihe Dong, Sercan Ö. Arik, Yan Liu, Tomas Pfister:
COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning. CoRR abs/2311.00886 (2023) - [i56]James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister:
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents. CoRR abs/2312.01279 (2023) - [i55]Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Jun Zhao, Wei Shen, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Xiaoran Fan, Shiliang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang:
LoRAMoE: Revolutionizing Mixture of Experts for Maintaining World Knowledge in Language Model Alignment. CoRR abs/2312.09979 (2023) - 2022
- [j30]Runzhuo Ma, Ashwin Ramaswamy, Jiashu Xu, Loc Trinh, Dani Kiyasseh, Timothy N. Chu, Elyssa Y. Wong, Ryan S. Lee, Ivan Rodriguez, Gina Demeo, Aditya Desai, Maxwell X. Otiato, Sidney I. Roberts, Jessica H. Nguyen, Jasper Laca, Yan Liu, Katarina Urbanova, Christian Wagner, Animashree Anandkumar, Jim C. Hu, Andrew J. Hung:
Surgical gestures as a method to quantify surgical performance and predict patient outcomes. npj Digit. Medicine 5 (2022) - [j29]Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui:
Energy system digitization in the era of AI: A three-layered approach toward carbon neutrality. Patterns 3(12): 100640 (2022) - [j28]Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu:
Toward Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data. ACM Trans. Spatial Algorithms Syst. 8(2): 1-30 (2022) - [c131]Sirisha Rambhatla, Zhengping Che, Yan Liu:
I-SEA: Importance Sampling and Expected Alignment-Based Deep Distance Metric Learning for Time Series Analysis and Embedding. AAAI 2022: 8045-8053 - [c130]Yizhou Zhang, Zhaoheng Zheng, Ram Nevatia, Yan Liu:
Improving Weakly Supervised Scene Graph Parsing through Object Grounding. ICPR 2022: 4058-4064 - [c129]Karishma Sharma, Emilio Ferrara, Yan Liu:
Characterizing Online Engagement with Disinformation and Conspiracies in the 2020 U.S. Presidential Election. ICWSM 2022: 908-919 - [c128]Karishma Sharma, Yizhou Zhang, Yan Liu:
COVID-19 Vaccine Misinformation Campaigns and Social Media Narratives. ICWSM 2022: 920-931 - [c127]Chuizheng Meng, Hao Niu, Guillaume Habault, Roberto Legaspi, Shinya Wada, Chihiro Ono, Yan Liu:
Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data. IJCAI 2022: 2189-2195 - [c126]James Enouen, Yan Liu:
Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection. NeurIPS 2022 - [c125]Yizhou Zhang, Defu Cao, Yan Liu:
Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media. NeurIPS 2022 - [c124]Hao Niu, Chuizheng Meng, Defu Cao, Guillaume Habault, Roberto Legaspi, Shinya Wada, Chihiro Ono, Yan Liu:
Mu2ReST: Multi-resolution Recursive Spatio-Temporal Transformer for Long-Term Prediction. PAKDD (1) 2022: 68-80 - [c123]Karishma Sharma, Emilio Ferrara, Yan Liu:
Construction of Large-Scale Misinformation Labeled Datasets from Social Media Discourse using Label Refinement. WWW 2022: 3755-3764 - [i54]Karishma Sharma, Emilio Ferrara, Yan Liu:
Construction of Large-Scale Misinformation Labeled Datasets from Social Media Discourse using Label Refinement. CoRR abs/2202.12413 (2022) - [i53]Chuizheng Meng, Sungyong Seo, Defu Cao, Sam Griesemer, Yan Liu:
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning. CoRR abs/2203.16797 (2022) - [i52]James Enouen, Yan Liu:
Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection. CoRR abs/2209.09326 (2022) - [i51]Yizhou Zhang, Defu Cao, Yan Liu:
Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media. CoRR abs/2210.07518 (2022) - [i50]Le Xie, Tong Huang, Xiangtian Zheng, Yan Liu, Mengdi Wang, Vijay Vittal, P. R. Kumar, Srinivas Shakkottai, Yi Cui:
Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality. CoRR abs/2211.04584 (2022) - [i49]Defu Cao, Yousef El-Laham, Loc Trinh, Svitlana Vyetrenko, Yan Liu:
DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift. CoRR abs/2211.11513 (2022) - 2021
- [j27]Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla, Chuizheng Meng, Yan Liu:
PolSIRD: Modeling Epidemic Spread Under Intervention Policies. J. Heal. Informatics Res. 5(3): 231-248 (2021) - [c122]Sirisha Rambhatla, Samantha Huang, Loc Trinh, Mengfei Zhang, Boyuan Long, Mingtao Dong, Vyom Unadkat, Haig Yenikomshian, Justin Gillenwater, Yan Liu:
DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning. AMIA 2021 - [c121]Nan Xu, Nitin Kamra, Yan Liu:
Treatment Recommendation with Preference-based Reinforcement Learning. ICBK 2021: 117-124 - [c120]Karishma Sharma, Xinran He, Sungyong Seo, Yan Liu:
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation. ICWSM 2021: 668-679 - [c119]Loc Trinh, Yan Liu:
An Examination of Fairness of AI Models for Deepfake Detection. IJCAI 2021: 567-574 - [c118]Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu:
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning. IJCAI 2021: 2943-2949 - [c117]Chuizheng Meng, Sirisha Rambhatla, Yan Liu:
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling. KDD 2021: 1202-1211 - [c116]Karishma Sharma, Yizhou Zhang, Emilio Ferrara, Yan Liu:
Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviours. KDD 2021: 1441-1451 - [c115]Yizhou Zhang, Karishma Sharma, Yan Liu:
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media. NeurIPS 2021: 3218-3231 - [c114]Nitin Kamra, Yan Liu:
Gradient-based optimization for multi-resource spatial coverage problems. UAI 2021: 1885-1894 - [c113]Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu:
Interpretable and Trustworthy Deepfake Detection via Dynamic Prototypes. WACV 2021: 1972-1982 - [i48]Chuizheng Meng, Loc Trinh, Nan Xu, Yan Liu:
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset. CoRR abs/2102.06761 (2021) - [i47]Michael Tsang, James Enouen, Yan Liu:
Interpretable Artificial Intelligence through the Lens of Feature Interaction. CoRR abs/2103.03103 (2021) - [i46]Loc Trinh, Yan Liu:
An Examination of Fairness of AI Models for Deepfake Detection. CoRR abs/2105.00558 (2021) - [i45]Chuizheng Meng, Sirisha Rambhatla, Yan Liu:
Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling. CoRR abs/2106.05223 (2021) - [i44]Karishma Sharma, Yizhou Zhang, Yan Liu:
COVID-19 Vaccines: Characterizing Misinformation Campaigns and Vaccine Hesitancy on Twitter. CoRR abs/2106.08423 (2021) - [i43]Karishma Sharma, Emilio Ferrara, Yan Liu:
Characterizing Online Engagement with Disinformation and Conspiracies in the 2020 U.S. Presidential Election. CoRR abs/2107.08319 (2021) - [i42]Xiangtian Zheng, Nan Xu, Loc Trinh, Dongqi Wu, Tong Huang, S. Sivaranjani, Yan Liu, Le Xie:
PSML: A Multi-scale Time-series Dataset for Machine Learning in Decarbonized Energy Grids. CoRR abs/2110.06324 (2021) - [i41]Yizhou Zhang, Karishma Sharma, Yan Liu:
VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media. CoRR abs/2110.15454 (2021) - 2020
- [j26]Rajesh Gupta, Yan Liu:
KDD 2020 Highlights. SIGKDD Explor. 22(2): 1 (2020) - [c112]Max Guangyu Li, Bo Jiang, Hao Zhu, Zhengping Che, Yan Liu:
Generative Attention Networks for Multi-Agent Behavioral Modeling. AAAI 2020: 7195-7202 - [c111]Karishma Sharma, Pinar Donmez, Enming Luo, Yan Liu, I. Zeki Yalniz:
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models. ECCV (27) 2020: 737-753 - [c110]Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu:
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. ICDE 2020: 1818-1821 - [c109]Sungyong Seo, Chuizheng Meng, Yan Liu:
Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics. ICLR 2020 - [c108]Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu:
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. ICLR 2020 - [c107]Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu:
Multi-agent Trajectory Prediction with Fuzzy Query Attention. NeurIPS 2020 - [c106]Michael Tsang, Sirisha Rambhatla, Yan Liu:
How does This Interaction Affect Me? Interpretable Attribution for Feature Interactions. NeurIPS 2020 - [e2]Rajesh Gupta, Yan Liu, Jiliang Tang, B. Aditya Prakash:
KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020. ACM 2020, ISBN 978-1-4503-7998-4 [contents] - [i40]Karishma Sharma, Pinar Donmez, Enming Luo, Yan Liu, I. Zeki Yalniz:
NoiseRank: Unsupervised Label Noise Reduction with Dependence Models. CoRR abs/2003.06729 (2020) - [i39]Karishma Sharma, Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Aastha Dua, Yan Liu:
Coronavirus on Social Media: Analyzing Misinformation in Twitter Conversations. CoRR abs/2003.12309 (2020) - [i38]Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu:
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning. CoRR abs/2006.08831 (2020) - [i37]Michael Tsang, Sirisha Rambhatla, Yan Liu:
How does this interaction affect me? Interpretable attribution for feature interactions. CoRR abs/2006.10965 (2020) - [i36]Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu:
Feature Interaction Interpretability: A Case for Explaining Ad-Recommendation Systems via Neural Interaction Detection. CoRR abs/2006.10966 (2020) - [i35]Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu:
Interpretable Deepfake Detection via Dynamic Prototypes. CoRR abs/2006.15473 (2020) - [i34]Karishma Sharma, Xinran He, Sungyong Seo, Yan Liu:
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation. CoRR abs/2008.03450 (2020) - [i33]Karishma Sharma, Emilio Ferrara, Yan Liu:
Identifying Coordinated Accounts in Disinformation Campaigns. CoRR abs/2008.11308 (2020) - [i32]Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu:
Multi-agent Trajectory Prediction with Fuzzy Query Attention. CoRR abs/2010.15891 (2020) - [i31]Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu:
Towards Accurate Spatiotemporal COVID-19 Risk Scores using High Resolution Real-World Mobility Data. CoRR abs/2012.07283 (2020)
2010 – 2019
- 2019
- [j25]Yolanda Gil, Suzanne A. Pierce, Hassan A. Babaie, Arindam Banerjee, Kirk D. Borne, Gary S. Bust, Michelle Cheatham, Imme Ebert-Uphoff, Carla P. Gomes, Mary C. Hill, John D. Horel, Leslie Hsu, Jim Kinter, Craig A. Knoblock, David M. Krum, Vipin Kumar, Pierre F. J. Lermusiaux, Yan Liu, Chris North, Victor Pankratius, Shanan Peters, Beth Plale, Allen Pope, Sai Ravela, Juan Restrepo, Aaron J. Ridley, Hanan Samet, Shashi Shekhar:
Intelligent systems for geosciences: an essential research agenda. Commun. ACM 62(1): 76-84 (2019) - [j24]Zemin Zheng, Mohammad Taha Bahadori, Yan Liu, Jinchi Lv:
Scalable Interpretable Multi-Response Regression via SEED. J. Mach. Learn. Res. 20: 107:1-107:34 (2019) - [j23]Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu:
Combating Fake News: A Survey on Identification and Mitigation Techniques. ACM Trans. Intell. Syst. Technol. 10(3): 21:1-21:42 (2019) - [c105]Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, Yan Liu:
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting. AAAI 2019: 3656-3663 - [c104]Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe:
Deep Fictitious Play for Games with Continuous Action Spaces. AAMAS 2019: 2042-2044 - [c103]Lingyu Zhang, Tianshu Song, Yongxin Tong, Zimu Zhou, Dan Li, Wei Ai, Lulu Zhang, Guobin Wu, Yan Liu, Jieping Ye:
Recommendation-based Team Formation for On-demand Taxi-calling Platforms. CIKM 2019: 59-68 - [c102]Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, Milind Tambe:
DeepFP for Finding Nash Equilibrium in Continuous Action Spaces. GameSec 2019: 238-258 - [c101]Max Guangyu Li, Bo Jiang, Zhengping Che, Xuefeng Shi, Mengyao Liu, Yiping Meng, Jieping Ye, Yan Liu:
DBUS: Human Driving Behavior Understanding System. ICCV Workshops 2019: 2436-2444 - [c100]Hanpeng Liu, Yaguang Li, Michael Tsang, Yan Liu:
CoSTCo: A Neural Tensor Completion Model for Sparse Tensors. KDD 2019: 324-334 - [i30]Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, Yan Liu:
Combating Fake News: A Survey on Identification and Mitigation Techniques. CoRR abs/1901.06437 (2019) - [i29]Zhengping Che, Max Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, Jieping Ye:
D2-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios. CoRR abs/1904.01975 (2019) - [i28]Xu Geng, Xiyu Wu, Lingyu Zhang, Qiang Yang, Yan Liu, Jieping Ye:
Multi-Modal Graph Interaction for Multi-Graph Convolution Network in Urban Spatiotemporal Forecasting. CoRR abs/1905.11395 (2019) - [i27]Conner Chyung, Michael Tsang, Yan Liu:
Extracting Interpretable Concept-Based Decision Trees from CNNs. CoRR abs/1906.04664 (2019) - 2018
- [j22]Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu:
Benchmarking deep learning models on large healthcare datasets. J. Biomed. Informatics 83: 112-134 (2018) - [c99]Nitin Kamra, Umang Gupta, Fei Fang, Yan Liu, Milind Tambe:
Policy Learning for Continuous Space Security Games Using Neural Networks. AAAI 2018: 1103-1112 - [c98]Sungyong Seo, Hau Chan, P. Jeffrey Brantingham, Jorja Leap, Phebe Vayanos, Milind Tambe, Yan Liu:
Partially Generative Neural Networks for Gang Crime Classification with Partial Information. AIES 2018: 257-263 - [c97]Dehua Cheng, Natali Ruchansky, Yan Liu:
Matrix completability analysis via graph k-connectivity. AISTATS 2018: 395-403 - [c96]Rose Yu, Max Guangyu Li, Yan Liu:
Tensor Regression Meets Gaussian Processes. AISTATS 2018: 482-490 - [c95]Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu:
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. ICLR (Poster) 2018 - [c94]Sungyong Seo, Arash Mohegh, George Ban-Weiss, Yan Liu:
Automatically Inferring Data Quality for Spatiotemporal Forecasting. ICLR (Poster) 2018 - [c93]Michael Tsang, Dehua Cheng, Yan Liu:
Detecting Statistical Interactions from Neural Network Weights. ICLR (Poster) 2018 - [c92]Zhengping Che, Sanjay Purushotham, Max Guangyu Li, Bo Jiang, Yan Liu:
Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series. ICML 2018: 783-792 - [c91]Feng Qian, ChengYue Gong, Karishma Sharma, Yan Liu:
Neural User Response Generator: Fake News Detection with Collective User Intelligence. IJCAI 2018: 3834-3840 - [c90]Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, Yan Liu:
Multi-task Representation Learning for Travel Time Estimation. KDD 2018: 1695-1704 - [c89]Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, Yan Liu:
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability. NeurIPS 2018: 5809-5818 - [c88]Yan Liu, Zhenhui Li, Wei Ai, Lingyu Zhang:
SIGIR 2018 Workshop on Intelligent Transportation Informatics. SIGIR 2018: 1441-1443 - [e1]Yi Chang, Chengxiang Zhai, Yan Liu, Yoelle Maarek:
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, WSDM 2018, Marina Del Rey, CA, USA, February 5-9, 2018. ACM 2018, ISBN 978-1-4503-5581-0 [contents] - [i26]Palash Goyal, Nitin Kamra, Xinran He, Yan Liu:
DynGEM: Deep Embedding Method for Dynamic Graphs. CoRR abs/1805.11273 (2018) - [i25]Michael Tsang, Youbang Sun, Dongxu Ren, Yan Liu:
Can I trust you more? Model-Agnostic Hierarchical Explanations. CoRR abs/1812.04801 (2018) - 2017
- [c87]Zhengping Che, Jennifer L. St. Sauver, Hongfang Liu, Yan Liu:
Deep Learning Solutions for Classifying Patients on Opioid Use. AMIA 2017 - [c86]Yan Liu:
Low-Rank tensor regression: Scalability and applications. CAMSAP 2017: 1-5 - [c85]Natali Ruchansky, Sungyong Seo, Yan Liu:
CSI: A Hybrid Deep Model for Fake News Detection. CIKM 2017: 797-806 - [c84]Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu:
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. ICDM 2017: 787-792 - [c83]Zhengping Che, Yan Liu:
Deep Learning Solutions to Computational Phenotyping in Health Care. ICDM Workshops 2017: 1100-1109 - [c82]Sanjay Purushotham, Wilka Carvalho, Tanachat Nilanon, Yan Liu:
Variational Recurrent Adversarial Deep Domain Adaptation. ICLR (Poster) 2017 - [c81]Sungyong Seo, Jing Huang, Hao Yang, Yan Liu:
Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction. RecSys 2017: 297-305 - [c80]Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu:
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. SDM 2017: 777-785 - [c79]Xinran He, Yan Liu:
Not Enough Data?: Joint Inferring Multiple Diffusion Networks via Network Generation Priors. WSDM 2017: 465-474 - [c78]Yan Liu, Sanjay Chawla:
Social Media Anomaly Detection: Challenges and Solutions. WSDM 2017: 817-818 - [p1]Zhengping Che, Sanjay Purushotham, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Robinder G. Khemani, Yan Liu:
Time Series Feature Learning with Applications to Health Care. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 389-409 - [r1]Rose Yu, Yan Liu:
Spatiotemporal Analysis of Social Media Data. Encyclopedia of GIS 2017: 2126-2133 - [i24]Zhengping Che, Yu Cheng, Zhaonan Sun, Yan Liu:
Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding. CoRR abs/1701.07474 (2017) - [i23]Natali Ruchansky, Sungyong Seo, Yan Liu:
CSI: A Hybrid Deep Model for Fake News. CoRR abs/1703.06959 (2017) - [i22]Michael Tsang, Dehua Cheng, Yan Liu:
Detecting Statistical Interactions from Neural Network Weights. CoRR abs/1705.04977 (2017) - [i21]Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu:
Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. CoRR abs/1707.01926 (2017) - [i20]Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, Yan Liu:
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records. CoRR abs/1709.01648 (2017) - [i19]Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu:
Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets. CoRR abs/1710.08531 (2017) - [i18]Nitin Kamra, Umang Gupta, Yan Liu:
Deep Generative Dual Memory Network for Continual Learning. CoRR abs/1710.10368 (2017) - [i17]Rose Yu, Max Guangyu Li, Yan Liu:
Tensor Regression Meets Gaussian Processes. CoRR abs/1710.11345 (2017) - 2016
- [j21]Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu:
A Survey on Social Media Anomaly Detection. SIGKDD Explor. 18(1): 1-14 (2016) - [j20]Yi Chang, Makoto Yamada, Antonio Ortega, Yan Liu:
Lifecycle Modeling for Buzz Temporal Pattern Discovery. ACM Trans. Knowl. Discov. Data 11(2): 20:1-20:24 (2016) - [j19]Huy Pham, Cyrus Shahabi, Yan Liu:
Inferring Social Strength from Spatiotemporal Data. ACM Trans. Database Syst. 41(1): 7:1-7:47 (2016) - [c77]Zhengping Che, Sanjay Purushotham, Robinder G. Khemani, Yan Liu:
Interpretable Deep Models for ICU Outcome Prediction. AMIA 2016 - [c76]Tanachat Nilanon, Sanjay Purushotham, Yan Liu:
Normal / Abnormal Heart Sound Recordings Classification Using Convolutional Neural Network. CinC 2016 - [c75]Rose Yu, Yan Liu:
Learning from Multiway Data: Simple and Efficient Tensor Regression. ICML 2016: 373-381 - [c74]Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada, Yan Liu:
Timeline Summarization from Social Media with Life Cycle Models. IJCAI 2016: 3698-3704 - [c73]Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu:
Latent Space Model for Road Networks to Predict Time-Varying Traffic. KDD 2016: 1525-1534 - [c72]Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros:
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling. NIPS 2016: 721-729 - [c71]Xinran He, Ke Xu, David Kempe, Yan Liu:
Learning Influence Functions from Incomplete Observations. NIPS 2016: 2065-2073 - [c70]Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu:
Geographic Segmentation via Latent Poisson Factor Model. WSDM 2016: 357-366 - [i16]Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu:
A Survey on Social Media Anomaly Detection. CoRR abs/1601.01102 (2016) - [i15]V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Rand Waltzman, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, V. G. Vinod Vydiswaran, Qiaozhu Mei, Tim Huang:
The DARPA Twitter Bot Challenge. CoRR abs/1601.05140 (2016) - [i14]Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu:
Latent Space Model for Road Networks to Predict Time-Varying Traffic. CoRR abs/1602.04301 (2016) - [i13]Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David A. Sontag, Yan Liu:
Recurrent Neural Networks for Multivariate Time Series with Missing Values. CoRR abs/1606.01865 (2016) - [i12]Qi Rose Yu, Yan Liu:
Learning from Multiway Data: Simple and Efficient Tensor Regression. CoRR abs/1607.02535 (2016) - [i11]Jie Chen, Dehua Cheng, Yan Liu:
On Bochner's and Polya's Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps. CoRR abs/1610.08861 (2016) - [i10]Xinran He, Ke Xu, David Kempe, Yan Liu:
Learning Influence Functions from Incomplete Observations. CoRR abs/1611.02305 (2016) - 2015
- [j18]Yan Liu:
Scalable Multivariate Time-Series Models for Climate Informatics. Comput. Sci. Eng. 17(6): 19-26 (2015) - [j17]Rose Yu, Xinran He, Yan Liu:
GLAD: Group Anomaly Detection in Social Media Analysis. ACM Trans. Knowl. Discov. Data 10(2): 18:1-18:22 (2015) - [c69]Dehua Cheng, Xinran He, Yan Liu:
Model Selection for Topic Models via Spectral Decomposition. AISTATS 2015 - [c68]David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel:
Causal Phenotype Discovery via Deep Networks. AMIA 2015 - [c67]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification. COLT 2015: 364-390 - [c66]Mohammad Taha Bahadori, David C. Kale, Yingying Fan, Yan Liu:
Functional Subspace Clustering with Application to Time Series. ICML 2015: 228-237 - [c65]Rose Yu, Dehua Cheng, Yan Liu:
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams. ICML 2015: 238-247 - [c64]Xinran He, Theodoros Rekatsinas, James R. Foulds, Lise Getoor, Yan Liu:
HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades. ICML 2015: 871-880 - [c63]Zhengping Che, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu:
Deep Computational Phenotyping. KDD 2015: 507-516 - [c62]Yan Liu, Sanjay Chawla:
Social Media Anomaly Detection: Challenges and Solutions. KDD 2015: 2317-2318 - [c61]David C. Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, Yan Liu:
Hierarchical Active Transfer Learning. SDM 2015: 514-522 - [i9]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Spectral Sparsification of Random-Walk Matrix Polynomials. CoRR abs/1502.03496 (2015) - [i8]Zhengping Che, Sanjay Purushotham, Robinder G. Khemani, Yan Liu:
Distilling Knowledge from Deep Networks with Applications to Healthcare Domain. CoRR abs/1512.03542 (2015) - 2014
- [j16]Gully Burns, Yolanda Gil, Yan Liu, Natalia Villanueva-Rosales, Sebastian Risi, Joel Lehman, Jeff Clune, Christian Lebiere, Paul S. Rosenbloom, Frank van Harmelen, James A. Hendler, Pascal Hitzler, Krzysztof Janowicz, Samarth Swarup:
Reports on the 2013 AAAI Fall Symposium Series. AI Mag. 35(2): 69-74 (2014) - [j15]Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
A general framework for scalable transductive transfer learning. Knowl. Inf. Syst. 38(1): 61-83 (2014) - [j14]Yi Chang, Lei Tang, Yoshiyuki Inagaki, Yan Liu:
What is Tumblr: a statistical overview and comparison. SIGKDD Explor. 16(1): 21-29 (2014) - [c60]David C. Kale, Dian Gong, Zhengping Che, Yan Liu, Gérard G. Medioni, Randall C. Wetzel, Patrick Ross:
An Examination of Multivariate Time Series Hashing with Applications to Health Care. ICDM 2014: 260-269 - [c59]Yi Chang, Makoto Yamada, Antonio Ortega, Yan Liu:
Ups and Downs in Buzzes: Life Cycle Modeling for Temporal Pattern Discovery. ICDM 2014: 749-754 - [c58]Dan Zhang, Yan Liu, Luo Si:
Which Tweets Will Be Headlines? A Hierarchical Bayesian Model for Bridging Social Media and Traditional Media. SNAKDD 2014: 5:1-5:9 - [c57]Mohammad Taha Bahadori, Yi Chang, Bo Long, Yan Liu:
Scalable Heterogeneous Transfer Ranking. BigMine 2014: 214-228 - [c56]Qi Rose Yu, Xinran He, Yan Liu:
GLAD: group anomaly detection in social media analysis. KDD 2014: 372-381 - [c55]Dehua Cheng, Mohammad Taha Bahadori, Yan Liu:
FBLG: a simple and effective approach for temporal dependence discovery from time series data. KDD 2014: 382-391 - [c54]Dehua Cheng, Yan Liu:
Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence. KDD 2014: 562-571 - [c53]Mohammad Taha Bahadori, Qi Rose Yu, Yan Liu:
Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning. NIPS 2014: 3491-3499 - [c52]Jingrui He, Yan Liu, Qiang Yang:
Linking Heterogeneous Input Spaces with Pivots for Multi-Task Learning. SDM 2014: 181-189 - [i7]Yi Chang, Lei Tang, Yoshiyuki Inagaki, Yan Liu:
What is Tumblr: A Statistical Overview and Comparison. CoRR abs/1403.5206 (2014) - [i6]Qi Yu, Xinran He, Yan Liu:
GLAD: Group Anomaly Detection in Social Media Analysis- Extended Abstract. CoRR abs/1410.1940 (2014) - [i5]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Scalable Parallel Factorizations of SDD Matrices and Efficient Sampling for Gaussian Graphical Models. CoRR abs/1410.5392 (2014) - [i4]Dehua Cheng, Xinran He, Yan Liu:
Analyzing the Number of Latent Topics via Spectral Decomposition. CoRR abs/1410.6466 (2014) - 2013
- [j13]Yi Chang, Anlei Dong, Pranam Kolari, Ruiqiang Zhang, Yoshiyuki Inagaki, Fernando Diaz, Hongyuan Zha, Yan Liu:
Improving recency ranking using twitter data. ACM Trans. Intell. Syst. Technol. 4(1): 4:1-4:24 (2013) - [c51]Gully A. P. C. Burns, Yolanda Gil, Yan Liu, Natalia Villanueva-Rosales:
Organizing Committee. AAAI Fall Symposia 2013 - [c50]Gully A. P. C. Burns, Yolanda Gil, Yan Liu, Natalia Villanueva-Rosales:
Preface. AAAI Fall Symposia 2013 - [c49]David C. Kale, Samuel Di, Yan Liu, Yolanda Gil:
Capturing Data Analytics Expertise with Visualizations in Workflows. AAAI Fall Symposia 2013 - [c48]Mohammad Taha Bahadori, Yan Liu, Eric P. Xing:
Fast structure learning in generalized stochastic processes with latent factors. KDD 2013: 284-292 - [c47]Yan Liu, Mohammad Taha Bahadori:
An Examination of Practical Granger Causality Inference. SDM 2013: 467-475 - [c46]Huy Pham, Cyrus Shahabi, Yan Liu:
EBM: an entropy-based model to infer social strength from spatiotemporal data. SIGMOD Conference 2013: 265-276 - [c45]Yi Chang, Xuanhui Wang, Qiaozhu Mei, Yan Liu:
Towards Twitter context summarization with user influence models. WSDM 2013: 527-536 - [i3]Jeon-Hyung Kang, Jun Ma, Yan Liu:
Transfer Topic Modeling with Ease and Scalability. CoRR abs/1301.5686 (2013) - 2012
- [c44]Mohammad Taha Bahadori, Yan Liu:
On Causality Inference in Time Series. AAAI Fall Symposium: Discovery Informatics 2012 - [c43]Huida Qiu, Yan Liu, Niranjan A. Subrahmanya, Weichang Li:
Granger Causality for Time-Series Anomaly Detection. ICDM 2012: 1074-1079 - [c42]Yan Liu, Mohammad Taha Bahadori, Hongfei Li:
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling. ICML 2012 - [c41]Sanjay Purushotham, Yan Liu:
Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems. ICML 2012 - [c40]Wenjun Zhou, Hongxia Jin, Yan Liu:
Community discovery and profiling with social messages. KDD 2012: 388-396 - [c39]Jeon-Hyung Kang, Jun Ma, Yan Liu:
Transfer Topic Modeling with Ease and Scalability. SDM 2012: 564-575 - [c38]Mohammad Taha Bahadori, Yan Liu:
Granger Causality Analysis in Irregular Time Series. SDM 2012: 660-671 - [i2]Sanjay Purushotham, Yan Liu, C.-C. Jay Kuo:
Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems. CoRR abs/1206.4684 (2012) - [i1]Yan Liu, Mohammad Taha Bahadori, Hongfei Li:
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling. CoRR abs/1206.4685 (2012) - 2011
- [j12]Yan Liu, Alexandru Niculescu-Mizil, Aurélie C. Lozano, Yong Lu:
Temporal Graphical Models for Cross-Species Gene Regulatory Network Discovery. J. Bioinform. Comput. Biol. 9(2): 231-250 (2011) - [j11]Jimeng Sun, Yan Liu, Jie Tang, Chid Apté:
Introduction to Special Issue on Large-Scale Data Mining. ACM Trans. Knowl. Discov. Data 5(2): 7:1 (2011) - [c37]Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan:
Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. AAAI 2011: 561-566 - [c36]Yi Chang, Ruiqiang Zhang, Srihari Reddy, Yan Liu:
Detecting Multilingual and Multi-Regional Query Intent in Web Search. AAAI 2011: 1134-1139 - [c35]Matheus Hauder, Yolanda Gil, Yan Liu:
A Framework for Efficient Data Analytics through Automatic Configuration and Customization of Scientific Workflows. eScience 2011: 379-386 - [c34]Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning. ICDM 2011: 61-70 - [c33]Yan Liu, Pei-yun Hseuh, Rick Lawrence, Steve Meliksetian, Claudia Perlich, Alejandro Veen:
Latent graphical models for quantifying and predicting patent quality. KDD 2011: 1145-1153 - [c32]Dan Zhang, Jingrui He, Yan Liu, Luo Si, Richard D. Lawrence:
Multi-view transfer learning with a large margin approach. KDD 2011: 1208-1216 - [c31]Dan Zhang, Yan Liu, Luo Si:
Serendipitous learning: learning beyond the predefined label space. KDD 2011: 1343-1351 - [c30]Dan Zhang, Yan Liu, Luo Si, Jian Zhang, Richard D. Lawrence:
Multiple Instance Learning on Structured Data. NIPS 2011: 145-153 - [c29]Matheus Hauder, Yolanda Gil, Ricky J. Sethi, Yan Liu, Hyunjoon Jo:
Making data analysis expertise broadly accessible through workflows. WORKS@SC 2011: 77-86 - 2010
- [j10]Saharon Rosset, Claudia Perlich, Grzegorz Swirszcz, Prem Melville, Yan Liu:
Medical data mining: insights from winning two competitions. Data Min. Knowl. Discov. 20(3): 439-468 (2010) - [c28]Xi Chen, Yan Liu, Han Liu, Jaime G. Carbonell:
Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis. AAAI 2010: 425-430 - [c27]Qihua Wang, Hongxia Jin, Yan Liu:
Collaboration analytics: mining work patterns from collaboration activities. CIKM 2010: 1861-1864 - [c26]Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan:
ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. ICDM Workshops 2010: 1265-1272 - [c25]Yan Liu, Alexandru Niculescu-Mizil, Aurélie C. Lozano, Yong Lu:
Learning Temporal Causal Graphs for Relational Time-Series Analysis. ICML 2010: 687-694
2000 – 2009
- 2009
- [j9]Aurélie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset:
Grouped graphical Granger modeling for gene expression regulatory networks discovery. Bioinform. 25(12) (2009) - [j8]Yan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele:
Conditional Graphical Models for Protein Structural Motif Recognition. J. Comput. Biol. 16(5): 639-657 (2009) - [c24]Jingrui He, Yan Liu, Richard D. Lawrence:
Graph-based transfer learning. CIKM 2009: 937-946 - [c23]Yan Liu, Pei-Yun Hsueh, Jennifer Lai, Mirweis Sangin, Marc-Antoine Nüssli, Pierre Dillenbourg:
Who is the expert? Analyzing gaze data to predict expertise level in collaborative applications. ICME 2009: 898-901 - [c22]Yan Liu, Alexandru Niculescu-Mizil, Wojciech Gryc:
Topic-link LDA: joint models of topic and author community. ICML 2009: 665-672 - [c21]Aurélie C. Lozano, Naoki Abe, Yan Liu, Saharon Rosset:
Grouped graphical Granger modeling methods for temporal causal modeling. KDD 2009: 577-586 - [c20]Aurélie C. Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan R. M. Hosking, Naoki Abe:
Spatial-temporal causal modeling for climate change attribution. KDD 2009: 587-596 - [c19]Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen:
Learning dynamic temporal graphs for oil-production equipment monitoring system. KDD 2009: 1225-1234 - [c18]Tsuyoshi Idé, Aurélie C. Lozano, Naoki Abe, Yan Liu:
Proximity-Based Anomaly Detection Using Sparse Structure Learning. SDM 2009: 97-108 - [c17]Alexandru Niculescu-Mizil, Claudia Perlich, Grzegorz Swirszcz, Vikas Sindhwani, Yan Liu, Prem Melville, Dong Wang, Jing Xiao, Jianying Hu, Moninder Singh, Wei Xiong Shang, Yanfeng Zhu:
Winning the KDD Cup Orange Challenge with Ensemble Selection. KDD Cup 2009: 23-34 - 2008
- [j7]Jun Yang, Rong Yan, Yan Liu, Eric P. Xing:
Harmonium Models for Video Classification. Stat. Anal. Data Min. 1(1): 23-37 (2008) - [j6]Claudia Perlich, Prem Melville, Yan Liu, Grzegorz Swirszcz, Richard D. Lawrence, Saharon Rosset:
Breast cancer identification: KDD CUP winner's report. SIGKDD Explor. 10(2): 39-42 (2008) - [c16]Jingrui He, Yan Liu, Richard D. Lawrence:
Graph-Based Rare Category Detection. ICDM 2008: 833-838 - 2007
- [j5]Yan Liu, Zhenzhen Kou:
Predicting who rated what in large-scale datasets. SIGKDD Explor. 9(2): 62-65 (2007) - [j4]Saharon Rosset, Claudia Perlich, Yan Liu:
Making the most of your data: KDD Cup 2007 "How Many Ratings" winner's report. SIGKDD Explor. 9(2): 66-69 (2007) - [c15]Yan Liu, Jun Yang, Alexander G. Hauptmann:
Undirected Graphical Models for Video Analysis and Classification. ICME 2007: 1495-1498 - [c14]Yan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele:
Protein Quaternary Fold Recognition Using Conditional Graphical Models. IJCAI 2007: 937-945 - [c13]Jingrui He, Jaime G. Carbonell, Yan Liu:
Graph-Based Semi-Supervised Learning as a Generative Model. IJCAI 2007: 2492-2497 - [c12]Katharina Probst, Rayid Ghani, Marko Krema, Andrew E. Fano, Yan Liu:
Semi-Supervised Learning of Attribute-Value Pairs from Product Descriptions. IJCAI 2007: 2838-2843 - [c11]Wojciech Gryc, Mary E. Helander, Richard D. Lawrence, Yan Liu, Claudia Perlich, Chandan K. Reddy, Saharon Rosset:
Looking for Great Ideas: Analyzing the Innovation Jam. WebKDD/SNA-KDD 2007: 21-39 - [c10]Andrew Arnold, Yan Liu, Naoki Abe:
Temporal causal modeling with graphical granger methods. KDD 2007: 66-75 - [c9]Jun Yang, Yan Liu, Eric P. Xing, Alexander G. Hauptmann:
Harmonium Models for Semantic Video Representation and Classification. SDM 2007: 378-389 - 2006
- [j3]Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan:
Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs). J. Comput. Biol. 13(2): 394-406 (2006) - [j2]Rayid Ghani, Katharina Probst, Yan Liu, Marko Krema, Andrew E. Fano:
Text mining for product attribute extraction. SIGKDD Explor. 8(1): 41-48 (2006) - [c8]Katharina Probst, Rayid Ghani, Marko Krema, Andy Fano, Yan Liu:
Extracting and Using Attribute-Value Pairs from Product Descriptions on the Web. WebMine 2006: 41-60 - 2005
- [c7]Yan Liu, Eric P. Xing, Jaime G. Carbonell:
Predicting protein folds with structural repeats using a chain graph model. ICML 2005: 513-520 - [c6]Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan:
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition. RECOMB 2005: 408-422 - 2004
- [j1]Yan Liu, Jaime G. Carbonell, Judith Klein-Seetharaman, Vanathi Gopalakrishnan:
Comparison of probabilistic combination methods for protein secondary structure prediction. Bioinform. 20(17): 3099-3107 (2004) - [c5]John D. Lafferty, Xiaojin Zhu, Yan Liu:
Kernel conditional random fields: representation and clique selection. ICML 2004 - [c4]Yan Liu, Jaime G. Carbonell, Judith Klein-Seetharaman, Vanathi Gopalakrishnan:
Context sensitive vocabulary and its application in protein secondary structure prediction. SIGIR 2004: 538-539 - 2003
- [c3]Yan Liu, Jaime G. Carbonell, Rong Jin:
A New Pairwise Ensemble Approach for Text Classification. ECML 2003: 277-288 - [c2]Rong Yan, Yan Liu, Rong Jin, Alexander G. Hauptmann:
On predicting rare classes with SVM ensembles in scene classification. ICASSP (3) 2003: 21-24 - 2002
- [c1]Yan Liu, Yiming Yang, Jaime G. Carbonell:
Boosting to correct inductive bias in text classification. CIKM 2002: 348-355
Coauthor Index
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