Liang Sun

ORCID

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 77

Top Venues

Arizona State University, Tempe, USA (PHD)

Education History

Arizona State University, Tempe, USA

PHD

Publications

Jiehui Zhou, Linxiao Yang, Xingyu Liu, Xinyue Gu, Liang Sun, Wei Chen
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect. KDD (2024)
Rui Ren, Jingbang Yang, Linxiao Yang, Xinyue Gu, Liang Sun
SLIM: a Scalable Light-weight Root Cause Analysis for Imbalanced Data in Microservice. ICSE Companion (2024)
Peisong Niu, Tian Zhou, Xue Wang, Liang Sun, Rong Jin
Attention as Robust Representation for Time Series Forecasting. CoRR (2024)
Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. CoRR (2024)
Nan Lu, Shu Liu, Qingsong Wen, Qiming Chen, Liang Sun, Yi Wang
Federated Domain Separation for Distributed Forecasting of Non-IID Household Loads. IEEE Trans. Smart Grid 15 (4) (2024)
Yifan Zhang, Weiqi Chen, Zhaoyang Zhu, Dalin Qin, Liang Sun, Xue Wang, Qingsong Wen, Zhang Zhang, Liang Wang, Rong Jin
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt. CoRR (2024)
Zhiqiang Zhou, Linxiao Yang, Qingsong Wen, Liang Sun
RobustTSVar: A Robust Time Series Variance Estimation Algorithm. ICASSP (2024)
Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen, Bingqing Peng, Liang Sun, Rong Jin
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting. KDD (2024)
Jiehui Zhou, Linxiao Yang, Xingyu Liu, Xinyue Gu, Liang Sun, Wei Chen
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect. CoRR (2024)
Linxiao Yang, Jingbang Yang, Liang Sun
Efficient Decision Rule List Learning via Unified Sequence Submodular Optimization. KDD (2024)
Yanjun Zhao, Tian Zhou, Chao Chen, Liang Sun, Yi Qian, Rong Jin
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting. CoRR (2024)
Rui Ren, Jingbang Yang, Linxiao Yang, Xinyue Gu, Liang Sun
SLIM: a Scalable Light-weight Root Cause Analysis for Imbalanced Data in Microservice. CoRR (2024)
Zhiqiang Zhou, Chaoli Zhang, Lingna Ma, Jing Gu, Huajie Qian, Qingsong Wen, Liang Sun, Peng Li, Zhimin Tang
AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes. AAAI (2023)
Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun
Transformers in Time Series: A Survey. IJCAI (2023)
Dalin Qin, Chenxi Wang, Qingsong Wen, Weiqi Chen, Liang Sun, Yi Wang
Personalized Federated DARTS for Electricity Load Forecasting of Individual Buildings. IEEE Trans. Smart Grid 14 (6) (2023)
Yanjun Zhao, Ziqing Ma, Tian Zhou, Mengni Ye, Liang Sun, Yi Qian
GCformer: An Efficient Solution for Accurate and Scalable Long-Term Multivariate Time Series Forecasting. CIKM (2023)
Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin
One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors. CoRR (2023)
Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Leandro Von Krannichfeldt, Yi Wang
Benchmarks and Custom Package for Electrical Load Forecasting. CoRR (2023)
Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. CoRR (2023)
Tian Zhou, PeiSong Niu, Xue Wang, Liang Sun, Rong Jin
Power Time Series Forecasting by Pretrained LM. CoRR (2023)
Linxiao Yang, Rui Ren, Xinyue Gu, Liang Sun
Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting. KDD (2023)
Yanjun Zhao, Ziqing Ma, Tian Zhou, Liang Sun, Mengni Ye, Yi Qian
GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting. CoRR (2023)
Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun
SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events. ICASSP (2023)
Linxiao Yang, Rui Ren, Xinyue Gu, Liang Sun
Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting. CoRR (2023)
Shikai Fang, Qingsong Wen, Shandian Zhe, Liang Sun
BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition. CoRR (2023)
Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Liang Sun, Rong Jin
SVQ: Sparse Vector Quantization for Spatiotemporal Forecasting. CoRR (2023)
Qingsong Wen, Linxiao Yang, Liang Sun
Robust Dominant Periodicity Detection for Time Series with Missing Data. CoRR (2023)
Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Qingsong Wen, Liang Sun
eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms. AAAI (2023)
Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. KDD (2023)
Binqing Wu, Weiqi Chen, Wengwei Wang, Bingqing Peng, Liang Sun, Ling Chen
WeatherGNN: Exploiting Complicated Relationships in Numerical Weather Prediction Bias Correction. CoRR (2023)
Zhaoyang Zhu, Weiqi Chen, Rui Xia, Tian Zhou, Peisong Niu, Bingqing Peng, Wenwei Wang, Hengbo Liu, Ziqing Ma, Xinyue Gu, Jin Wang, Qiming Chen, Linxiao Yang, Qingsong Wen, Liang Sun
Energy forecasting with robust, flexible, and explainable machine learning algorithms. AI Mag. 44 (4) (2023)
Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Yi Wang
DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model. CoRR (2023)
Hengbo Liu, Ziqing Ma, Linxiao Yang, Tian Zhou, Rui Xia, Yi Wang, Qingsong Wen, Liang Sun
SaDI: A Self-adaptive Decomposed Interpretable Framework for Electric Load Forecasting under Extreme Events. CoRR (2023)
Pengwei Liu, Wenwei Wang, Bingqing Peng, Binqing Wu, Liang Sun
DSAF: A Dual-Stage Adaptive Framework for Numerical Weather Prediction Downscaling. CoRR (2023)
Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin
One Fits All: Power General Time Series Analysis by Pretrained LM. NeurIPS (2023)
Yi-Fan Zhang, Qingsong Wen, Xue Wang, Weiqi Chen, Liang Sun, Zhang Zhang, Liang Wang, Rong Jin, Tieniu Tan
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling. CoRR (2023)
Xiaomin Song, Qingsong Wen, Yan Li, Liang Sun
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection. CoRR (2022)
Huajie Qian, Qingsong Wen, Liang Sun, Jing Gu, Qiulin Niu, Zhimin Tang
RobustScaler: QoS-Aware Autoscaling for Complex Workloads. CoRR (2022)
Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. ICML (2022)
Tian Zhou, Jianqing Zhu, Xue Wang, Ziqing Ma, Qingsong Wen, Liang Sun, Rong Jin
TreeDRNet: A Robust Deep Model for Long Term Time Series Forecasting. CoRR (2022)
Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun
Transformers in Time Series: A Survey. CoRR (2022)
Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. NeurIPS (2022)
Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun
Robust Time Series Analysis and Applications: An Industrial Perspective. KDD (2022)
Yan Li, Rui Xia, Chunchen Liu, Liang Sun
A Hybrid Causal Structure Learning Algorithm for Mixed-Type Data. AAAI (2022)
Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun
Netrca: An Effective Network Fault Cause Localization Algorithm. ICASSP (2022)
Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. CoRR (2022)
Huajie Qian, Qingsong Wen, Liang Sun, Jing Gu, Qiulin Niu, Zhimin Tang
RobustScaler: QoS-Aware Autoscaling for Complex Workloads. ICDE (2022)
Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. CIKM (2022)
Weiqi Chen, Wenwei Wang, Bingqing Peng, Qingsong Wen, Tian Zhou, Liang Sun
Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting. KDD (2022)
Xiaomin Song, Qingsong Wen, Yan Li, Liang Sun
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection. CIKM (2022)
Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. CoRR (2022)
Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. CoRR (2022)
Tian Zhou, Ziqing Ma, Xue Wang, Qingsong Wen, Liang Sun, Tao Yao, Wotao Yin, Rong Jin
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting. NeurIPS (2022)
Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun
NetRCA: An Effective Network Fault Cause Localization Algorithm. CoRR (2022)
Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. CoRR (2022)
Linxiao Yang, Qingsong Wen, Bo Yang, Liang Sun
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition. ICASSP (2021)
Yingying Zhang, Zhengxiong Guan, Huajie Qian, Leili Xu, Hengbo Liu, Qingsong Wen, Liang Sun, Junwei Jiang, Lunting Fan, Min Ke
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms. CIKM (2021)
Linxiao Yang, Qingsong Wen, Bo Yang, Liang Sun
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition. CoRR (2021)
Qingsong Wen, Liang Sun, Fan Yang, Xiaomin Song, Jingkun Gao, Xue Wang, Huan Xu
Time Series Data Augmentation for Deep Learning: A Survey. IJCAI (2021)
Yingying Zhang, Zhengxiong Guan, Huajie Qian, Leili Xu, Hengbo Liu, Qingsong Wen, Liang Sun, Junwei Jiang, Lunting Fan, Min Ke
CloudRCA: A Root Cause Analysis Framework for Cloud Computing Platforms. CoRR (2021)
Qingyang Xu, Qingsong Wen, Liang Sun
Two-Stage Framework for Seasonal Time Series Forecasting. CoRR (2021)
Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu
RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection. SIGMOD Conference (2021)
Fan Yang, Kai He, Linxiao Yang, Hongxia Du, Jingbang Yang, Bo Yang, Liang Sun
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach. NeurIPS (2021)
Qingyang Xu, Qingsong Wen, Liang Sun
Two-Stage Framework for Seasonal Time Series Forecasting. ICASSP (2021)
Qingsong Wen, Zhengzhi Ma, Liang Sun
On Robust Variance Filtering and Change of Variance Detection. ICASSP (2020)
Qingsong Wen, Zhe Zhang, Yan Li, Liang Sun
Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns. KDD (2020)
Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicities Detection. CoRR (2020)
Qingsong Wen, Liang Sun, Xiaomin Song, Jingkun Gao, Xue Wang, Huan Xu
Time Series Data Augmentation for Deep Learning: A Survey. CoRR (2020)
Jingkun Gao, Xiaomin Song, Qingsong Wen, Pichao Wang, Liang Sun, Huan Xu
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks. CoRR (2020)
Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Jian Tan
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering. CoRR (2019)
Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. KDD (2019)
Ming Lin, Xiaomin Song, Qi Qian, Hao Li, Liang Sun, Shenghuo Zhu, Rong Jin
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement. CoRR (2019)
Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series. AAAI (2019)
Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
Which Factorization Machine Modeling is Better: A Theoretical Answer with Optimal Guarantee. CoRR (2019)
Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Jian Tan
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering. IJCAI (2019)
Ming Lin, Shuang Qiu, Jieping Ye, Xiaomin Song, Qi Qian, Liang Sun, Shenghuo Zhu, Rong Jin
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee. AAAI (2019)
Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series. CoRR (2018)
Jun Liu, Liang Sun, Jieping Ye
Projection onto A Nonnegative Max-Heap. NIPS (2011)
Liang Sun, Shuiwang Ji, Jieping Ye
Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 33 (1) (2011)
Shuai Huang, Jing Li, Liang Sun, Jieping Ye, Adam Fleisher, Teresa Wu, Kewei Chen, Eric Reiman
Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation. NeuroImage 50 (3) (2010)
Liang Sun, Betul Ceran, Jieping Ye
A scalable two-stage approach for a class of dimensionality reduction techniques. KDD (2010)
Zheng Zhao, Liang Sun, Shipeng Yu, Huan Liu, Jieping Ye
Multiclass Probabilistic Kernel Discriminant Analysis. IJCAI (2009)
Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. NIPS (2009)
Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, Jieping Ye
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation. KDD (2009)
Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye
On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. IJCAI (2009)
Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye
Efficient Recovery of Jointly Sparse Vectors. NIPS (2009)
Liang Sun, Shuiwang Ji, Jieping Ye
A least squares formulation for a class of generalized eigenvalue problems in machine learning. ICML (2009)
Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, Jieping Ye
gene expression patterns using a controlled vocabulary. Bioinform. 24 (17) (2008)
Liang Sun, Shuiwang Ji, Jieping Ye
Hypergraph spectral learning for multi-label classification. KDD (2008)
Liang Sun, Shuiwang Ji, Jieping Ye
A least squares formulation for canonical correlation analysis. ICML (2008)
Liang Sun, Shuiwang Ji, Jieping Ye
Adaptive diffusion kernel learning from biological networks for protein function prediction. BMC Bioinform. 9 (2008)
Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye
Multi-label Multiple Kernel Learning. NIPS (2008)

Liang Sun.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Liang Sun