
Yan Liu 0002
Person information
- affiliation: University of Southern California, Computer Science Department, Los Angeles, CA, USA
- affiliation: IBM T. J. Watson Research Center, CA, USA
- affiliation: Carnegie Mellon University, Language Technologies Institute, Pittsburgh, PA, USA
Other persons with the same name
- Yan Liu — disambiguation page
- Yan Liu 0001
— 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 — National University of Singapore, Singapore
- Yan Liu 0013
— University of Queensland, School of Geography Planning and Environmental Management
- 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
— Imperial College London, Department of Electrical and Electronic Engineering, UK
- Yan Liu 0017 — Xerox Research Centre Euorpe (and 1 more)
- Yan Liu 0018 — Xidian University, National Lab of Radar Signal Processing
- 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 0023 — University of Queensland, School of Earth Sciences, Centre for Geoscience Computing
- 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 — Northwestern Polytechnical University, School of Computer Science, Xi'an, China
- Yan Liu 0046 — Anhui University, School of Mathematical Sciences, Hefei, China
- Yan Liu 0047 — Chinese University of Hong Kong, Department of Information Engineering, Hong Kong
- 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
Refine list

refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2020
- [j23]Rajesh Gupta, Yan Liu:
KDD 2020 Highlights. SIGKDD Explor. 22(2): 1 (2020) - [c100]Max Guangyu Li, Bo Jiang, Hao Zhu, Zhengping Che, Yan Liu:
Generative Attention Networks for Multi-Agent Behavioral Modeling. AAAI 2020: 7195-7202 - [c99]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 - [c98]Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu:
Multi-agent Trajectory Prediction with Fuzzy Query Attention. NeurIPS 2020 - [c97]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] - [i33]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) - [i32]Sungyong Seo, Chuizheng Meng, Sirisha Rambhatla, Yan Liu:
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning. CoRR abs/2006.08831 (2020) - [i31]Michael Tsang, Sirisha Rambhatla, Yan Liu:
How does this interaction affect me? Interpretable attribution for feature interactions. CoRR abs/2006.10965 (2020) - [i30]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) - [i29]Loc Trinh, Michael Tsang, Sirisha Rambhatla, Yan Liu:
Interpretable Deepfake Detection via Dynamic Prototypes. CoRR abs/2006.15473 (2020) - [i28]Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu:
Multi-agent Trajectory Prediction with Fuzzy Query Attention. CoRR abs/2010.15891 (2020)
2010 – 2019
- 2019
- [j22]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) - [c96]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 - [c95]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 - [c94]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 - [c93]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 - [c92]Hanpeng Liu, Yaguang Li, Michael Tsang, Yan Liu:
CoSTCo: A Neural Tensor Completion Model for Sparse Tensors. KDD 2019: 324-334 - [i27]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) - [i26]Conner Chyung, Michael Tsang, Yan Liu:
Extracting Interpretable Concept-Based Decision Trees from CNNs. CoRR abs/1906.04664 (2019) - 2018
- [j21]Sanjay Purushotham, Chuizheng Meng, Zhengping Che
, Yan Liu:
Benchmarking deep learning models on large healthcare datasets. J. Biomed. Informatics 83: 112-134 (2018) - [c91]Nitin Kamra, Umang Gupta, Fei Fang, Yan Liu, Milind Tambe:
Policy Learning for Continuous Space Security Games Using Neural Networks. AAAI 2018: 1103-1112 - [c90]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 - [c89]Dehua Cheng, Natali Ruchansky, Yan Liu:
Matrix completability analysis via graph k-connectivity. AISTATS 2018: 395-403 - [c88]Rose Yu, Max Guangyu Li, Yan Liu:
Tensor Regression Meets Gaussian Processes. AISTATS 2018: 482-490 - [c87]Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu:
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. ICLR (Poster) 2018 - [c86]Sungyong Seo, Arash Mohegh, George Ban-Weiss, Yan Liu:
Automatically Inferring Data Quality for Spatiotemporal Forecasting. ICLR (Poster) 2018 - [c85]Michael Tsang, Dehua Cheng, Yan Liu:
Detecting Statistical Interactions from Neural Network Weights. ICLR (Poster) 2018 - [c84]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 - [c83]Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, Yan Liu:
Multi-task Representation Learning for Travel Time Estimation. KDD 2018: 1695-1704 - [c82]Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, Yan Liu:
Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability. NeurIPS 2018: 5809-5818 - [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] - [i25]Palash Goyal, Nitin Kamra, Xinran He, Yan Liu:
DynGEM: Deep Embedding Method for Dynamic Graphs. CoRR abs/1805.11273 (2018) - [i24]Michael Tsang, Youbang Sun, Dongxu Ren, Yan Liu:
Can I trust you more? Model-Agnostic Hierarchical Explanations. CoRR abs/1812.04801 (2018) - 2017
- [c81]Zhengping Che, Jennifer L. St. Sauver, Hongfang Liu, Yan Liu:
Deep Learning Solutions for Classifying Patients on Opioid Use. AMIA 2017 - [c80]Yan Liu:
Low-Rank tensor regression: Scalability and applications. CAMSAP 2017: 1-5 - [c79]Natali Ruchansky, Sungyong Seo, Yan Liu:
CSI: A Hybrid Deep Model for Fake News Detection. CIKM 2017: 797-806 - [c78]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 - [c77]Zhengping Che, Yan Liu:
Deep Learning Solutions to Computational Phenotyping in Health Care. ICDM Workshops 2017: 1100-1109 - [c76]Sanjay Purushotham, Wilka Carvalho, Tanachat Nilanon, Yan Liu:
Variational Recurrent Adversarial Deep Domain Adaptation. ICLR (Poster) 2017 - [c75]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 - [c74]Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, Yan Liu:
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting. SDM 2017: 777-785 - [c73]Xinran He, Yan Liu:
Not Enough Data?: Joint Inferring Multiple Diffusion Networks via Network Generation Priors. WSDM 2017: 465-474 - [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 - [i23]Zhengping Che, Yu Cheng, Zhaonan Sun, Yan Liu:
Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding. CoRR abs/1701.07474 (2017) - [i22]Natali Ruchansky, Sungyong Seo, Yan Liu:
CSI: A Hybrid Deep Model for Fake News. CoRR abs/1703.06959 (2017) - [i21]Michael Tsang, Dehua Cheng, Yan Liu:
Detecting Statistical Interactions from Neural Network Weights. CoRR abs/1705.04977 (2017) - [i20]Yaguang Li, Rose Yu, Cyrus Shahabi, Yan Liu:
Graph Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting. CoRR abs/1707.01926 (2017) - [i19]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) - [i18]Sanjay Purushotham, Chuizheng Meng, Zhengping Che, Yan Liu:
Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets. CoRR abs/1710.08531 (2017) - [i17]Nitin Kamra, Umang Gupta, Yan Liu:
Deep Generative Dual Memory Network for Continual Learning. CoRR abs/1710.10368 (2017) - [i16]Rose Yu, Max Guangyu Li, Yan Liu:
Tensor Regression Meets Gaussian Processes. CoRR abs/1710.11345 (2017) - 2016
- [j20]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) - [j19]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) - [j18]Huy Pham, Cyrus Shahabi, Yan Liu:
Inferring Social Strength from Spatiotemporal Data. ACM Trans. Database Syst. 41(1): 7:1-7:47 (2016) - [c72]Zhengping Che, Sanjay Purushotham, Robinder G. Khemani, Yan Liu:
Interpretable Deep Models for ICU Outcome Prediction. AMIA 2016 - [c71]Tanachat Nilanon, Sanjay Purushotham, Yan Liu:
Normal / Abnormal Heart Sound Recordings Classification Using Convolutional Neural Network. CinC 2016 - [c70]Rose Yu, Yan Liu:
Learning from Multiway Data: Simple and Efficient Tensor Regression. ICML 2016: 373-381 - [c69]Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada, Yan Liu:
Timeline Summarization from Social Media with Life Cycle Models. IJCAI 2016: 3698-3704 - [c68]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 - [c67]Dehua Cheng, Richard Peng, Yan Liu, Ioakeim Perros:
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling. NIPS 2016: 721-729 - [c66]Xinran He, Ke Xu, David Kempe, Yan Liu:
Learning Influence Functions from Incomplete Observations. NIPS 2016: 2065-2073 - [c65]Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, Yan Liu:
Geographic Segmentation via Latent Poisson Factor Model. WSDM 2016: 357-366 - [i15]Rose Yu, Huida Qiu, Zhen Wen, Ching-Yung Lin, Yan Liu:
A Survey on Social Media Anomaly Detection. CoRR abs/1601.01102 (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
- [j17]Yan Liu:
Scalable Multivariate Time-Series Models for Climate Informatics. Comput. Sci. Eng. 17(6): 19-26 (2015) - [j16]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) - [c64]Dehua Cheng, Xinran He, Yan Liu:
Model Selection for Topic Models via Spectral Decomposition. AISTATS 2015 - [c63]David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel:
Causal Phenotype Discovery via Deep Networks. AMIA 2015 - [c62]Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, Shang-Hua Teng:
Efficient Sampling for Gaussian Graphical Models via Spectral Sparsification. COLT 2015: 364-390 - [c61]Mohammad Taha Bahadori, David C. Kale, Yingying Fan, Yan Liu:
Functional Subspace Clustering with Application to Time Series. ICML 2015: 228-237 - [c60]Rose Yu, Dehua Cheng, Yan Liu:
Accelerated Online Low Rank Tensor Learning for Multivariate Spatiotemporal Streams. ICML 2015: 238-247 - [c59]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 - [c58]Zhengping Che
, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu:
Deep Computational Phenotyping. KDD 2015: 507-516 - [c57]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
- [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) - [c56]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 - [c55]Yi Chang, Makoto Yamada, Antonio Ortega, Yan Liu:
Ups and Downs in Buzzes: Life Cycle Modeling for Temporal Pattern Discovery. ICDM 2014: 749-754 - [c54]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 - [c53]Mohammad Taha Bahadori, Yi Chang, Bo Long, Yan Liu:
Scalable Heterogeneous Transfer Ranking. BigMine 2014: 214-228 - [c52]Qi Rose Yu, Xinran He, Yan Liu:
GLAD: group anomaly detection in social media analysis. KDD 2014: 372-381 - [c51]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 - [c50]Dehua Cheng, Yan Liu:
Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence. KDD 2014: 562-571 - [c49]Mohammad Taha Bahadori, Qi Rose Yu, Yan Liu:
Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning. NIPS 2014: 3491-3499 - [c48]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) - [c47]David C. Kale, Samuel Di, Yan Liu, Yolanda Gil:
Capturing Data Analytics Expertise with Visualizations in Workflows. AAAI Fall Symposia 2013 - [c46]Mohammad Taha Bahadori, Yan Liu, Eric P. Xing:
Fast structure learning in generalized stochastic processes with latent factors. KDD 2013: 284-292 - [c45]Yan Liu, Mohammad Taha Bahadori:
An Examination of Practical Granger Causality Inference. SDM 2013: 467-475 - [c44]Huy Pham, Cyrus Shahabi, Yan Liu:
EBM: an entropy-based model to infer social strength from spatiotemporal data. SIGMOD Conference 2013: 265-276 - [c43]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
- [c42]Mohammad Taha Bahadori, Yan Liu:
On Causality Inference in Time Series. AAAI Fall Symposium: Discovery Informatics 2012 - [c41]Huida Qiu, Yan Liu, Niranjan A. Subrahmanya, Weichang Li:
Granger Causality for Time-Series Anomaly Detection. ICDM 2012: 1074-1079 - [c40]Yan Liu, Mohammad Taha Bahadori, Hongfei Li:
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling. ICML 2012 - [c39]Sanjay Purushotham, Yan Liu:
Collaborative Topic Regression with Social Matrix Factorization for Recommendation Systems. ICML 2012 - [c38]Jeon-Hyung Kang, Jun Ma, Yan Liu:
Transfer Topic Modeling with Ease and Scalability. SDM 2012: 564-575 - [c37]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, Aurelie 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) - [c36]Yi Chang, Ruiqiang Zhang, Srihari Reddy, Yan Liu:
Detecting Multilingual and Multi-Regional Query Intent in Web Search. AAAI 2011 - [c35]Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan:
Transfer Latent Semantic Learning: Microblog Mining with Less Supervision. AAAI 2011 - [c34]Matheus Hauder, Yolanda Gil
, Yan Liu:
A Framework for Efficient Data Analytics through Automatic Configuration and Customization of Scientific Workflows. eScience 2011: 379-386 - [c33]Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning. ICDM 2011: 61-70 - [c32]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 - [c31]Dan Zhang, Jingrui He, Yan Liu, Luo Si, Richard D. Lawrence:
Multi-view transfer learning with a large margin approach. KDD 2011: 1208-1216 - [c30]Dan Zhang, Yan Liu, Luo Si:
Serendipitous learning: learning beyond the predefined label space. KDD 2011: 1343-1351 - [c29]Dan Zhang, Yan Liu, Luo Si, Jian Zhang, Richard D. Lawrence:
Multiple Instance Learning on Structured Data. NIPS 2011: 145-153 - 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 - [c27]