2023
- Large Scale Financial Time Series Forecasting with Multi-faceted Model
Defu Cao, Yixiang Zheng, Parisa Hassanzadeh, Simran Lamba, Xiaomo Liu, Yan Liu
ICAIF, 2023 - Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning
Yizhou Zhang, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong, Heifeng Chen, Yan Liu
NeurIPS, 2023 - Capturing Cross-Platform Interaction for Identifying Coordinated Accounts of Misinformation Campaigns
Yizhou Zhang, Karishma Sharma, Yan Liu
ICAIF, 2023 - Self-supervised Sim-to-Real Kinematics Reconstruction for Video-based Assessment of Intraoperative Suturing Skills
Loc Trinh, Tim Chu, Zijun Cui, Anand Malpani, Cherine Yang, Istabraq Dalieh, Alvin Hui, Oscar Gomez, Andrew Hung, Yan Liu
MICCAI, 2023 - Transferable and Interpretable Treatment Effectiveness Prediction for Ovarian Cancer via Multimodal Deep Learning
Emily Nguyen, Zijun Cui, Georgia Kokaraki, Joseph Carlson, Yan Liu
AMIA, 2023 - SVGformer: Representation Learning for Continuous Vector Graphics using Transformers
Defu Cao, Zhaowen Wang, Jose Echevarria, Yan Liu
CVPR, 2023 - Coupled Multiwavelet Neural Operator Learning for Coupled Partial Differential Equations
Xiongye Xiao, Defu Cao, Ruochen Yang, Gaurav Gupta, Gengshuo Liu, Chenzhong Yin, Radu Balan, Paul Bogdan
ICLR, 2023 - Time-delayed Multivariate Time Series Predictions
Hao Niu, Guillaume Habault, Roberto Legaspi, Chuizheng Meng, Defu Cao, Shinya Wada, Chihiro Ono, Yan Liu
SDM, 2023
2022
- Sparse Interaction Additive Networks via Feature Interaction Detection and Sparse Selection
James Enouen, Yan Liu
Advances in Neural Information Processing Systems 35 (NeurIPS 2022) - Physics-Informed Long-Sequence Spatiotemporal Forecasting with Multi-Resolution Data
Chuizheng Meng, Hao Niu, Guillaume Habault, Roberto Legaspi, Shinya Wada, Chihiro Ono, Yan Liu
IJCAI, 2022 - DSLOB: A Synthetic Limit Order Book Dataset for Benchmarking Forecasting Algorithms under Distributional Shift
Defu Cao, Yousef El-Laham, Loc Trinh, Svitlana Vyetrenko, Yan Liu
NeurIPS, 2022 - Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset
Chuizheng Meng, Loc Trinh, Nan Xu, James Enouen, Yan Liu
Scientific Reports, 2022 - Estimating Treatment Effects in Continuous Time with Hidden Confounders
Defu Cao, James Enouen, Yan Liu
ICML, 2022 - When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Chuizheng Meng, Sungyong Seo, Defu Cao, Sam Griesemer, Yan Liu
Arxiv, 2022 - Hardware Reusability Optimization for High-Level Synthesis of Component-Based Processors
Xianhua Liu, Defu Cao, Qinshu Chen
IEEE ICCCAS, 2022 - Counterfactual Neural Temporal Point Process for Estimating Causal Influence of Misinformation on Social Media
Yizhou Zhang, Defu Cao, Yan Liu
NeurIPS, 2022 - Enhancing Self-Attention with Knowledge-Assisted Attention Maps
Jiangang Bai, Yujing Wang, Hong Sun, Ruonan Wu, Tianmeng Yang, Pengfei Tang, Wei Shen, Defu Cao, Mingliang Zhang, Yaming Yang, Jing Bai, Yunhai Tong, Hao Sun, Ruofei Zhang
NAACL, 2022 - Mu2ReST: Multi-Resolution Recursive Spatio-Temporal Transformer for Long-Term Prediction
Hao Niu, Chuizheng Meng, Defu Cao, Guillaume Habault, Roberto Legaspi, Shinya Wada, Chihiro Ono, Yan Liu
PAKDD, 2022
2021
- Spectral Temporal Graph Neural Network for Trajectory Prediction
Defu Cao, Jiachen Li, Hengbo Ma, Masayoshi Tomizuka
ICRA, 2021 - Treatment Recommendation with Preference-based Reinforcement Learning
Nan Xu, Nitin Kamra, Yan Liu
The 12th IEEE International Conference on Big Knowledge (ICBK), 2021 - VigDet: Knowledge Informed Neural Temporal Point Process for Coordination Detection on Social Media
Yizhou Zhang, Karishma Sharma, Yan Liu
Advances in Neural Information Processing Systems (NeurIPS), 2021 - Road to automating robotic suturing skills assessment: Battling mislabeling of the ground truth
Andrew J Hung, Sirisha Rambhatla, Daniel I Sanford, Nilay Pachauri, Erik Vanstrum, Jessica H Nguyen, Yan Liu
Surgery, 2021 - Towards Accurate Spatiotemporal COVID-19 Risk Scores using High Resolution Real-World Mobility Data
Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu
ACM Transactions on Spatial Algorithms and Systems (TSAS), 2021 - Automating suturing skills assessment with a limited surgeon dataset: Meta learning
Andrew J. Hung, Sirisha Rambhatla, Daniel I. Sanford, Nilay Pachauri, Jessica H. Nguyen, Yan Liu
American Urology Association, 2021 - PolSIRD: Modeling Epidemic Spread Under Intervention Policies
Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla, Chuizheng Meng, Yan Liu
Journal of Healthcare Informatics Research (JHIR), 2021 - Gradient-based Optimization for Multi-resource Spatial Coverage
Nitin Kamra, Yan Liu
The Conference on Uncertainty in Artificial Intelligence (UAI), 2021 - Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
Chuizheng Meng, Sirisha Rambhatla, Yan Liu
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2021 - Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviours
Karishma Sharma, Yizhou Zhang, Emilio Ferrara, Yan Liu
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2021 - Simulating Continuous-time Human Mobility Trajectories
Nan Xu, Loc Trinh, Sirisha Rambhatla, Samuel Assefa, Jiahao Chen, Zhen Zeng, Yan Liu
Deep Learning For Simulation Workshop, ICLR 2021. - An Examination of Fairness of AI Models for Deepfake Detection
Loc Trinh, Yan Liu
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI), 2021 - Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning
Sungyong Seo , Chuizheng Meng , Sirisha Rambhatla, Yan Liu
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI), 2021 - Network Inference from a Mixture of Diffusion Models for Fake News Mitigation
Karishma Sharma, Xinran He, Sungyong Seo, Yan Liu
Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2021
2020
- Multi-agent Trajectory Prediction with Fuzzy Query Attention
Nitin Kamra, Hao Zhu, Dweep Trivedi, Ming Zhang, Yan Liu
Advances in Neural Information Processing Systems (NeurIPS), 2020 - Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics
Sungyong Seo, Chuizheng Meng, and Yan Liu
International Conference on Learning Representations (ICLR), 2020
[Paper] - Generative Attention Networks for Multi-Agent Behavioral Modeling
Guangyu Li, Bo Jiang, Hao Zhu, Zhengping Che, and Yan Liu
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 - How does this interaction affect me? Interpretable attribution for feature interactions
Michael Tsang, Sirisha Rambhatla, Yan Liu
Advances in Neural Information Processing Systems (NeurIPS), 2020 - Extracting and Leveraging Feature Interaction Interpretations
Michael Tsang, Dehua Cheng, Hanpeng Liu, Xue Feng, Eric Zhou, Yan Liu
International Conference on Learning Representations (ICLR), 2020 - Predicting Origin- Destination Flow via Multi-Perspective Graph Convolutional Network
Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu
IEEE International Conference on Data Engineering (ICDE), 2020 - NoiseRank: Unsupervised Label Noise Reduction with Dependence Models
Karishma Sharma, Pinar Donmez, Enming Luo, Yan Liu, I. Zeki Yalniz
Proceedings of the European Conference on Computer Vision (ECCV), 2020
2019
- CoSTCo: A Neural Tensor Completion Model for Sparse Tensors
Hanpeng Liu, Yaguang Li, Michael Tsang, and Yan Liu
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019 - Current status of artificial intelligence applications in Urology and its potential to influence clinical practice
Jian Chen, Daphne Remulla, Jessica H Nguyen, Aastha Dua, Yan Liu, Prokar Dasgupta, and Andrew J Hung
BJU international, 2019 - DeepFP for Finding Nash Equilibrium in Continuous Action Spaces
Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, and Milind Tambe
Decision and Game Theory for Security (GameSec), 2019
[Paper] - Data-driven Temporal Attribution Discovery of Temperature Dynamics based on Attention Networks
Sungyong Seo, Jiachen Zhang, George Ban-Weiss, and Yan Liu
9th International Workshop on Climate Informatics (CI), 2019 - Deep Fictitious Play for Games with Continuous Action Spaces
Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, and Milind Tambe
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), 2019
[Paper] - Structure-informed Graph Auto-encoder for Relational Inference and Simulation
Yaguang Li, Chuizheng Meng, Cyrus Shahabi, and Yan Liu
ICML Workshops on Learning and Reasoning with Graph-Structured Representations, 2019
[Paper] - DBUS: Human Driving Behavior Understanding System
Max Guangyu Li, Bo Jiang, Zhengping Che, Xuefeng Shi, Mengyao Liu, Yiping Meng, Jieping Ye, and Yan Liu
Proceedings of the IEEE International Conference on Computer Vision Workshops, 2019
[Paper] - D $^ 2$-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios
Zhengping Che, Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, and Jieping Ye
arXiv preprint arXiv:1904.01975, 2019
[Paper] - Combating fake news: A survey on identification and mitigation techniques
Karishma Sharma, Feng Qian, He Jiang, Natali Ruchansky, Ming Zhang, and Yan Liu
ACM Transactions on Intelligent Systems and Technology (TIST), 2019 - Differentiable Physics-informed Graph Networks
Sungyong Seo and Yan Liu
ICLR Workshop on Representation Learning on Graphs and Manifolds Workshop (ICLR-RLGM), 2019
[Paper]
2018
- Neural User Response Generator: Fake News Detection with Collective User Intelligence
Feng Qian, Chengyue Gong, Karishma Sharma, and Yan Liu
International Joint Conferences on Artificial Intelligence (IJCAI), Jul 2018
[Paper] - Policy Learning for Continuous Space Security Games Using Neural Networks
Nitin Kamra, Umang Gupta, Fei Fang, Yan Liu, and Milind Tambe
AAAI Conference on Artificial Intelligence (AAAI), Feb 2018
[Paper] - Neural interaction transparency (NIT): disentangling learned interactions for improved interpretability
Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, and Yan Liu
Advances in Neural Information Processing Systems, 2018 - Transparency by Disentangling Interactions
Michael Tsang, Hanpeng Liu, Sanjay Purushotham, Pavankumar Murali, and Yan Liu
Advances in Neural Information Processing systems (NIPS), 2018 - Utilizing machine learning and automated performance metrics to evaluate robot-assisted radical prostatectomy performance and predict outcomes
Andrew J Hung, Jian Chen, Zhengping Che, Tanachat Nilanon, Anthony Jarc, Micha Titus, Paul J Oh, Inderbir S Gill, and Yan Liu
Journal of Endourology, 2018 - Recurrent neural networks for multivariate time series with missing values
Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, and Yan Liu
Scientific Reports, 2018 - Partially Generative Neural Networks for Gang Crime Classification with Partial Information
Sungyong Seo, Hau Chan, P Jeffrey Brantingham, Jorja Leap, Phebe Vayanos, Milind Tambe, and Yan Liu
AAAI/ACM Conference on Artificial Intelligence, Ethics and Society (AIES), 2018 - Detecting Statistical Interactions from Neural Network Weights
Michael Tsang, Dehua Cheng, and Yan Liu
International Conference on Learning Representations (ICLR), 2018 - Utilization of Machine Learning and Automated Performance Metrics to Evaluate Robot-assisted Radical Prostatectomy Performance and Predict Patient Outcomes
Andrew Hung, Jian Chen, Zhengping Che, Tanachat Nilanon, Anthony Jarc, Liheng Guo, Paul Oh, Inderbir Gill, and Yan Liu
Journal of Urology, 2018 - Multi-task representation learning for travel time estimation
Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, and Yan Liu
International Conference on Knowledge Discovery and Data Mining (KDD), 2018
[Paper] - Matrix completability analysis via graph k-connectivity
Dehua Cheng, Natali Ruchansky, and Yan Liu
International Conference on Artificial Intelligence and Statistics (AISTATS), 2018 - Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Yaguang Li, Rose Yu, Cyrus Shahabi, and Yan Liu
International Conference on Learning Representations (ICLR), 2018
[Paper] - Automatically Inferring Data Quality for Spatiotemporal Forecasting
Sungyong Seo, Arash Mohegh, George Ban-Weiss, and Yan Liu
International Conference on Learning Representations (ICLR), 2018
[Paper] - Tensor Regression Meets Gaussian Processes
Rose Yu, Guangyu Li, and Yan Liu
International Conference on Artificial Intelligence and Statistics (AISTATS), 2018 - Benchmarking Deep Learning Models on Large Healthcare Datasets
Sanjay Purushotham, Chuizheng Meng, Zhengping Che, and Yan Liu
Journal of Biomedical Informatics, 2018 - Hierarchical Deep Generative Models for Multi-Rate Multivariate Time Series
Zhengping Che, Sanjay Purushotham, Guangyu Li, Bo Jiang, and Yan Liu
International Conference on Machine Learning (ICML), 2018
2017
- Deep Generative Dual Memory Network for Continual Learning
Nitin Kamra, Umang Gupta, and Yan Liu
arXiv preprint, arXiv:1710.10368, Oct 2017
[Paper] - DynGEM: Deep Embedding Method for Dynamic Graphs
Nitin Kamra, Palash Goyal, Xinran He, and Yan Liu
IJCAI International Workshop on Representation Learning for Graphs (ReLiG), Aug 2017
[Paper] - Handling Continuous Space Security Games with Neural Networks
Nitin Kamra, Fei Fang, Debarun Kar, Yan Liu, and Milind Tambe
IJCAI International Workshop on A.I. in Security (IWAISe), Aug 2017
[Paper] - Variational Recurrent Adversarial Deep Domain Adaptation
Sanjay Purushotham, Wilka Carvalho, Tanachat Nilanon, and Yan Liu
International Conference on Learning Representations (ICLR), Apr 2017 - CSI: A hybrid deep model for fake news detection
Natali Ruchansky, Sungyong Seo, and Yan Liu
International Conference on Information and Knowledge Management (CIKM), 2017
[Paper] - Deep learning: A generic approach for extreme condition traffic forecasting
Rose Yu, Yaguang Li, Cyrus Shahabi, Ugur Demiryurek, and Yan Liu
SIAM International Conference on Data Mining (SDM), 2017
[Paper] - Boosting deep learning risk prediction with generative adversarial networks for electronic health records
Zhengping Che, Yu Cheng, Shuangfei Zhai, Zhaonan Sun, and Yan Liu
International Conference on Data Mining (ICDM), 2017 - Graph Convolutional Autoencoder with Recurrent Neural Networks for Spatiotemporal Forecasting
Sungyong Seo, Arash Mohegh, George Ban-Weiss, and Yan Liu
7th International Workshop on Climate Informatics (CI), 2017
[Paper] - Time series feature learning with applications to health care
Zhengping Che, Sanjay Purushotham, David Kale, Wenzhe Li, Mohammad Taha Bahadori, Robinder Khemani, and Yan Liu
2017 - Deep Multi-Instance Learning for Concept Annotation from Medical Time Series Data
Sanjay Purushotham, Zhengping Che, Bo Jiang, and Yan Liu
NIPS Workshop on Machine Learning for Health (ML4H), 2017 - Representation learning of users and items for review rating prediction using attention-based convolutional neural network
Sungyong Seo, Jing Huang, Hao Yang, and Yan Liu
SDM Workshop on Machine Learning Methods for Recommender Systems (MLRec), 2017 - Not enough data?: Joint inferring multiple diffusion networks via network generation priors
Xinran He and Yan Liu
International Conference on Web Search and Data Mining (WSDM), 2017 - DECADE: A Deep Metric Learning Model for Multivariate Time Series
Zhengping Che, Xinran He, Ke Xu, and Yan Liu
SIGKDD Workshop on Mining and Learning from Time Series, 2017 - Deep Learning Solutions for Classifying Patients on Opioid Use
Zhengping Che, Jennifer St Sauver, Hongfang Liu, and Yan Liu
AMIA Annual Symposium (AMIA), 2017 - A pilot study in using deep learning to predict limited life expectancy in women with recurrent cervical cancer
Koji Matsuo, Sanjay Purushotham, Aida Moeini, Guangyu Li, Hiroko Machida, Yan Liu, and Lynda D Roman
American Journal of Obstetrics & Gynecology, 2017 - Data Quality Network for Spatiotemporal Forecasting
Sungyong Seo, Yan Liu, Arash Mohegh, and George Ban-Weiss
NeurIPS Workshop on Deep Learning for Physical Sciences Workshop (NeurIPS-DLPS), 2017
[Paper] - Interpretable convolutional neural networks with dual local and global attention for review rating prediction
Sungyong Seo, Jing Huang, Hao Yang, and Yan Liu
International Conference on Recommender Systems (RecSys), 2017
[Paper]
2016
- Normal/Abnormal Heart Sound Recordings Classification Using Convolutional Neural Network
Tanachat Nilanon, Jiayu Yao, Junheng Hao, Sanjay Purushotham, and Yan Liu
Computing in Cardiology Conference (CinC), Sep 2016 - Learning influence functions from incomplete observations
Xinran He, Ke Xu, David Kempe, and Yan Liu
Advances in Neural Information Processing systems (NIPS), 2016 - Interpretable deep models for ICU outcome prediction
Zhengping Che, Sanjay Purushotham, Robinder Khemani, and Yan Liu
AMIA Annual Symposium (AMIA), 2016 - SPALS: Fast alternating least squares via implicit leverage scores sampling
Dehua Cheng, Richard Peng, Yan Liu, and Ioakeim Perros
Advances in Neural Information Processing systems (NIPS), 2016 - Geographic segmentation via latent poisson factor model
Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi, and Yan Liu
International Conference on Web Search and Data Mining (WSDM), 2016 - A survey on social media anomaly detection
Rose Yu, Huida Qiu, Zhen Wen, ChingYung Lin, and Yan Liu
ACM SIGKDD Explorations Newsletter, 2016 - Timeline Summarization from Social Media with Life Cycle Models.
Yi Chang, Jiliang Tang, Dawei Yin, Makoto Yamada, and Yan Liu
International Joint Conferences on Artificial Intelligence (IJCAI), 2016 - On Bochner’s and Polya’s Characterizations of Positive-Definite Kernels and the Respective Random Feature Maps
Jie Chen, Dehua Cheng, and Yan Liu
arXiv preprint arXiv:1610.08861, 2016 - Latent space model for road networks to predict time-varying traffic
Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, and Yan Liu
International Conference on Knowledge Discovery and Data Mining (KDD), 2016 - Learning from multiway data: Simple and efficient tensor regression
Rose Yu and Yan Liu
International Conference on Machine Learning (ICML), 2016
2015
- Functional subspace clustering with application to time series
Mohammad Taha Bahadori, David Kale, Yingying Fan, and Yan Liu
International Conference on Machine Learning (ICML), 2015 - Efficient sampling for Gaussian graphical models via spectral sparsification
Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, and Shang-Hua Teng
Conference on Learning Theory (COLT), 2015 - Hawkestopic: A joint model for network inference and topic modeling from text-based cascades
Xinran He, Theodoros Rekatsinas, James Foulds, Lise Getoor, and Yan Liu
International Conference on Machine Learning (ICML), 2015 - Model selection for topic models via spectral decomposition
Dehua Cheng, Xinran He, and Yan Liu
International Conference on Artificial Intelligence and Statistics (AISTATS), 2015 - Spectral sparsification of random-walk matrix polynomials
Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, and Shang-Hua Teng
arXiv preprint arXiv:1502.03496, 2015 - Accelerated online low rank tensor learning for multivariate spatiotemporal streams
Rose Yu, Dehua Cheng, and Yan Liu
International Conference on Machine Learning (ICML), 2015 - Hierarchical active transfer learning
David Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, and Yan Liu
SIAM International Conference on Data Mining (SDM), 2015 - GLAD: group anomaly detection in social media analysis
Rose Yu, Xinran He, and Yan Liu
Transactions on Knowledge Discovery from Data (TKDD), 2015
2014
- Analyzing the Number of Latent Topics via Spectral Decomposition
Dehua Cheng, Xinran He, and Yan Liu
Stat, 2014 - Fast multivariate spatio-temporal analysis via low rank tensor learning
Mohammad Taha Bahadori, Qi Rose Yu, and Yan Liu
Advances in Neural Information Processing systems (NIPS), 2014 - FBLG: a simple and effective approach for temporal dependence discovery from time series data
Dehua Cheng, Mohammad Taha Bahadori, and Yan Liu
International Conference on Knowledge Discovery and Data Mining (KDD), 2014 - Scalable parallel factorizations of SDD matrices and efficient sampling for gaussian graphical models
Dehua Cheng, Yu Cheng, Yan Liu, Richard Peng, and Shang-Hua Teng
arXiv preprint arXiv:1410.5392, 2014 - Bayesian regularization via graph Laplacian
Fei Liu, Sounak Chakraborty, Fan Li, Yan Liu, Aurelie C Lozano, and others
Bayesian Analysis, 2014 - Parallel gibbs sampling for hierarchical dirichlet processes via gamma processes equivalence
Dehua Cheng and Yan Liu
International Conference on Knowledge Discovery and Data Mining (KDD), 2014 - Ups and downs in buzzes: Life cycle modeling for temporal pattern discovery
Yi Chang, Makoto Yamada, Antonio Ortega, and Yan Liu
International Conference on Data Mining (ICDM), 2014 - Linking heterogeneous input spaces with pivots for multi-task learning
Jingrui He, Yan Liu, and Qiang Yang
SIAM International Conference on Data Mining (SDM), 2014 - Computational discovery of physiomes in critically ill children using deep learning
David Kale, Zhengping Che, Yan Liu, and R Wetzel
AMIA DMMI Workshop, 2014 - An examination of multivariate time series hashing with applications to health care
David C Kale, Dian Gong, Zhengping Che, Yan Liu, Gerard Medioni, Randall Wetzel, and Patrick Ross
International Conference on Data Mining (ICDM), 2014
Pre-2014
- Accelerating active learning with transfer learning
David Kale and Yan Liu
International Conference on Data Mining (ICDM), 2013 - Fast structure learning in generalized stochastic processes with latent factors
Mohammad Taha Bahadori, Yan Liu, and Eric P Xing
International Conference on Knowledge Discovery and Data Mining (KDD), 2013 - An examination of practical granger causality inference
Mohammad Taha Bahadori and Yan Liu
SIAM International Conference on Data Mining (SDM), 2013 - Collaborative topic regression with social matrix factorization for recommendation systems
Sanjay Purushotham, Yan Liu, and C-C Jay Kuo
International Conference on Machine Learning (ICML), 2012 - Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Series Modeling
Yan Liu, Mohammad Taha Bahadori, and Hongfei Li
International Conference on Machine Learning (ICML), 2012 - Transfer topic modeling with ease and scalability
Jeon-hyung Kang, Jun Ma, and Yan Liu
SIAM International Conference on Data Mining (SDM), 2012 - Granger causality for time-series anomaly detection
Huida Qiu, Yan Liu, Niranjan A Subrahmanya, and Weichang Li
International Conference on Data Mining (ICDM), 2012 - Granger causality analysis in irregular time series
Mohammad Taha Bahadori and Yan Liu
SIAM International Conference on Data Mining (SDM), 2012 - Community discovery and profiling with social messages
Wenjun Zhou, Hongxia Jin, and Yan Liu
International Conference on Knowledge Discovery and Data Mining (KDD), 2012 - Transfer Latent Semantic Learning: Microblog Mining with Less Supervision.
Dan Zhang, Yan Liu, Richard D Lawrence, and Vijil Chenthamarakshan
AAAI Conference on Artificial Intelligence (AAAI), 2011 - Detecting Multilingual and Multi-Regional Query Intent in Web Search.
Yi Chang, Ruiqiang Zhang, Srihari Reddy, and Yan Liu
AAAI Conference on Artificial Intelligence (AAAI), 2011 - A framework for efficient data analytics through automatic configuration and customization of scientific workflows
Matheus Hauder, Yolanda Gil, and Yan Liu
International Conference on eScience (eScience), 2011 - Multi-view transfer learning with a large margin approach
Dan Zhang, Jingrui He, Yan Liu, Luo Si, and Richard Lawrence
International Conference on Knowledge Discovery and Data Mining (KDD), 2011 - Learning with minimum supervision: A general framework for transductive transfer learning
Mohammad Taha Bahadori, Yan Liu, and Dan Zhang
International Conference on Data Mining (ICDM), 2011 - Multiple instance learning on structured data
Dan Zhang, Yan Liu, Luo Si, Jian Zhang, and Richard D Lawrence
Advances in Neural Information Processing Systems (NIPS), 2011 - Latent graphical models for quantifying and predicting patent quality
Yan Liu, Pei-yun Hseuh, Rick Lawrence, Steve Meliksetian, Claudia Perlich, and Alejandro Veen
International Conference on Knowledge Discovery and Data Mining (KDD), 2011 - Temporal graphical models for cross-species gene regulatory network discovery
Yan Liu, Alexandru Niculescu-Mizil, Aurelie Lozano, and Yong Lu
Journal of Bioinformatics and Computational Biology, 2011 - Serendipitous learning: learning beyond the predefined label space
Dan Zhang, Yan Liu, and Luo Si
International Conference on Knowledge Discovery and Data Mining (KDD), 2011 - Collaboration analytics: mining work patterns from collaboration activities
Qihua Wang, Hongxia Jin, and Yan Liu
International Conference on Information and Knowledge Management (CIKM), 2010 - Medical data mining: insights from winning two competitions
Saharon Rosset, Claudia Perlich, Grzergorz Świrszcz, Prem Melville, and Yan Liu
Data Mining and Knowledge Discovery, 2010 - Learning Spatial-Temporal Varying Graphs with Applications to Climate Data Analysis.
Xi Chen, Yan Liu, Han Liu, and Jaime G Carbonell
AAAI Conference on Artificial Intelligence (AAAI), 2010 - Learning temporal causal graphs for relational time-series analysis
Yan Liu, Alexandru Niculescu-Mizil, Aurelie C Lozano, and Yong Lu
International Conference on Machine Learning (ICML), 2010 - Topic-link LDA: joint models of topic and author community
Yan Liu, Alexandru Niculescu-Mizil, and Wojciech Gryc
International Conference on Machine Learning (ICML), 2009 - Grouped graphical Granger modeling methods for temporal causal modeling
Aurelie C Lozano, Naoki Abe, Yan Liu, and Saharon Rosset
International Conference on Knowledge Discovery and Data Mining (KDD), 2009 - Learning dynamic temporal graphs for oil-production equipment monitoring system
Yan Liu, Jayant R Kalagnanam, and Oivind Johnsen
International Conference on Knowledge Discovery and Data Mining (KDD), 2009 - Proximity-based anomaly detection using sparse structure learning
Tsuyoshi Idé, Aurelie C Lozano, Naoki Abe, and Yan Liu
SIAM International Conference on Data Mining (SDM), 2009 - Spatial-temporal causal modeling for climate change attribution
Aurelie C Lozano, Hongfei Li, Alexandru Niculescu-Mizil, Yan Liu, Claudia Perlich, Jonathan Hosking, and Naoki Abe
International Conference on Knowledge Discovery and Data Mining (KDD), 2009 - Who is the expert? Analyzing gaze data to predict expertise level in collaborative applications
Yan Liu, Pei-Yun Hsueh, Jennifer Lai, Mirweis Sangin, Marc-Antoine Nussli, and Pierre Dillenbourg
International Conference on Multimedia and Expo (ICME), 2009 - Winner’s Report: KDD CUP Breast Cancer Identification
Claudia Perlich, Prem Melville, Yan Liu, Grzegorz Swirszcz, Richard Lawrence, and Saharon Rosset
SIGKDD Workshop on Mining Medical Data, 2008 - Graph-based rare category detection
Jingrui He, Yan Liu, and Richard Lawrence
International Conference on Data Mining (ICDM), 2008 - Intelligent system for workforce classification
Yan Liu, Zhenzhen Kou, Claudia Perlich, and Richard Lawrence
SIGKDD Workshop on Data Mining for Business Applications, 2008 - Finding New Customers Using Unstructured and Structured Data
Prem Melville, Yan Liu, Richard Lawrence, Ildar Khabibrakhmanov, Cezar Pendus, and Timothy Bowden
International Conference on Knowledge Discovery and Data Mining (KDD), Aug 2007 - Temporal causal modeling with graphical granger methods
Andrew Arnold, Yan Liu, and Naoki Abe
International Conference on Knowledge Discovery and Data Mining (KDD), 2007 - Harmonium models for semantic video representation and classification
Jun Yang, Yan Liu, Eric P Xing, and Alexander G Hauptmann
SIAM International Conference on Data Mining (SDM), 2007 - Making the most of your data: KDD Cup 2007 How Many Ratings winner’s report
Saharon Rosset, Claudia Perlich, and Yan Liu
ACM SIGKDD Explorations Newsletter, 2007 - Predicting who rated what in large-scale datasets
Yan Liu and Zhenzhen Kou
ACM SIGKDD Explorations Newsletter, 2007 - Protein Quaternary Fold Recognition Using Conditional Graphical Models.
Yan Liu, Jaime G Carbonell, Vanathi Gopalakrishnan, and Peter Weigele
International Joint Conferences on Artificial Intelligence (IJCAI), 2007 - Semi-Supervised Learning of Attribute-Value Pairs from Product Descriptions.
Katharina Probst, Rayid Ghani, Marko Krema, Andrew E Fano, and Yan Liu
International Joint Conferences on Artificial Intelligence (IJCAI), 2007 - Text mining for product attribute extraction
Rayid Ghani, Katharina Probst, Yan Liu, Marko Krema, and Andrew Fano
International Conference on Knowledge Discovery and Data Mining (KDD), 2006 - Protein fold recognition using segmentation conditional random fields (SCRFs)
Yan Liu, Jaime Carbonell, Peter Weigele, and Vanathi Gopalakrishnan
Journal of Computational Biology, 2006 - Predicting protein folds with structural repeats using a chain graph model
Yan Liu, Eric P Xing, and Jaime Carbonell
International Conference on Machine Learning (ICML), 2005 - Segmentation conditional random fields (SCRFs): A new approach for protein fold recognition
Yan Liu, Jaime Carbonell, Peter Weigele, and Vanathi Gopalakrishnan
Annual International Conference on Research in Computational Molecular Biology, 2005 - Comparison of probabilistic combination methods for protein secondary structure prediction
Yan Liu, Jaime Carbonell, Judith Klein-Seetharaman, and Vanathi Gopalakrishnan
Bioinformatics, 2004 - Kernel conditional random fields: representation and clique selection
John Lafferty, Xiaojin Zhu, and Yan Liu
International Conference on Machine Learning (ICML), 2004 - A new boosting algorithm using input-dependent regularizer
Rong Jin, Yan Liu, Luo Si, Jaime G Carbonell, and Alexander Hauptmann
International Conference on Machine Learning (ICML), 2003 - On predicting rare classes with SVM ensembles in scene classification
Rong Yan, Yan Liu, Rong Jin, and Alex Hauptmann
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2003 - A new pairwise ensemble approach for text classification
Yan Liu, Jaime Carbonell, and Rong Jin
European Conference on Machine Learning (ECML), 2003 - Boosting to correct inductive bias in text classification
Yan Liu, Yiming Yang, and Jaime Carbonell
Conference on Information and Knowledge Management (CIKM), 2002
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