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ORCIDLiang Sun 0001
Person information
- affiliation: Alibaba Group, Bellevue, WA, USA
- affiliation (former): Arizona State University, Tempe, AZ, USA
Other persons with the same name
- Liang Sun — disambiguation page
- Liang Sun 0002
![[0000-0002-4002-6876]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-4002-6876")
— New Mexico State University, Mechanical and Aerospace Engineering, Las Cruces, NM, USA (and 3 more) - Liang Sun 0003 — Dalian University of Technology, College of Computer Science and Technology, China (and 2 more)
- Liang Sun 0004 — University of Science and Technology Beijing, School of Automation and Electrical Engineering, China (and 1 more)
- Liang Sun 0005 — USDA Agricultural Research Service, Washington, DC, USA (and 2 more)
- Liang Sun 0006 — Dalian University of Technology, School of Software, China
- Liang Sun 0007 — Beihang University, School of Electronic and Information Engineering, Beijing, China (and 3 more)
- Liang Sun 0008 — China University of Mining and Technology, Xuzhou, China
- Liang Sun 0009 — Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, China
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2020 – today
- 2024
[j7]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): 4271-4283 (2024)- [c55]Chaoli Zhang, Yingying Zhang, Lanshu Peng, Qingsong Wen, Yiyuan Yang, Chong-Jiong Fan, Minqi Jiang, Lunting Fan, Liang Sun:
Advancing Multivariate Time Series Anomaly Detection: A Comprehensive Benchmark with Real-World Data from Alibaba Cloud. CIKM 2024: 5410-5414 - [c54]Zhiqiang Zhou, Linxiao Yang, Qingsong Wen, Liang Sun:
RobustTSVar: A Robust Time Series Variance Estimation Algorithm. ICASSP 2024: 161-165 - [c53]Kexin Zhang, Qingsong Wen, Chaoli Zhang, Liang Sun, Yong Liu:
Skip-Step Contrastive Predictive Coding for Time Series Anomaly Detection. ICASSP 2024: 7065-7069 - [c52]Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun:
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies. ICLR 2024 - [c51]Shikai Fang, Qingsong Wen, Yingtao Luo, Shandian Zhe, Liang Sun:
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition. ICML 2024 - [c50]Linxiao Yang, Yunze Tong, Xinyue Gu, Liang Sun:
Explain Temporal Black-Box Models via Functional Decomposition. ICML 2024 - [c49]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: 328-330 - [c48]Binqing Wu, Weiqi Chen, Wengwei Wang, Bingqing Peng, Liang Sun, Ling Chen:
WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction. IJCAI 2024: 2433-2441 - [c47]Linxiao Yang, Jingbang Yang, Liang Sun:
Efficient Decision Rule List Learning via Unified Sequence Submodular Optimization. KDD 2024: 3758-3769 - [c46]Jiehui Zhou, Linxiao Yang, Xingyu Liu, Xinyue Gu, Liang Sun, Wei Chen:
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect. KDD 2024: 4619-4630 - [c45]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: 5532-5543 - [c44]Qiang Li, Yiqiao Sun, Linsey Pang, Liang Sun, Qingsong Wen:
Stable Synthetic Control with Anomaly Detection for Causal Inference. SDM 2024: 770-778 - [i46]Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun:
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies. CoRR abs/2402.02032 (2024) - [i45]Peisong Niu, Tian Zhou, Xue Wang, Liang Sun, Rong Jin:
Attention as Robust Representation for Time Series Forecasting. CoRR abs/2402.05370 (2024) - [i44]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 abs/2402.05823 (2024) - [i43]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 abs/2402.05830 (2024) - [i42]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 abs/2403.14949 (2024) - [i41]Rui Ren, Jingbang Yang, Linxiao Yang, Xinyue Gu, Liang Sun:
SLIM: a Scalable Light-weight Root Cause Analysis for Imbalanced Data in Microservice. CoRR abs/2405.20848 (2024) - [i40]Jiehui Zhou, Linxiao Yang, Xingyu Liu, Xinyue Gu, Liang Sun, Wei Chen:
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect. CoRR abs/2407.01004 (2024) - [i39]Dalin Qin, Yehui Li, Weiqi Chen, Zhaoyang Zhu, Qingsong Wen, Liang Sun, Pierre Pinson, Yi Wang:
Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts. CoRR abs/2409.19718 (2024) - [i38]Yangyang Guo, Yanjun Zhao, Sizhe Dang, Tian Zhou, Liang Sun, Yi Qian:
Less is more: Embracing sparsity and interpolation with Esiformer for time series forecasting. CoRR abs/2410.05726 (2024) - [i37]Peiyuan Liu, Tian Zhou, Liang Sun, Rong Jin:
Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting. CoRR abs/2410.06560 (2024) - [i36]Zhixian Wang, Linxiao Yang, Liang Sun, Qingsong Wen, Yi Wang:
Task-oriented Time Series Imputation Evaluation via Generalized Representers. CoRR abs/2410.06652 (2024) - 2023
- [j6]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): 377-393 (2023) - [j5]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): 4888-4901 (2023) - [c43]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: 15621-15629 - [c42]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: 15630-15638 - [c41]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: 3464-3473 - [c40]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: 1-5 - [c39]Qingsong Wen, Linxiao Yang, Liang Sun:
Robust Dominant Periodicity Detection for Time Series with Missing Data. ICASSP 2023: 1-5 - [c38]Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun:
Transformers in Time Series: A Survey. IJCAI 2023: 6778-6786 - [c37]Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. KDD 2023: 3033-3045 - [c36]Linxiao Yang, Rui Ren, Xinyue Gu, Liang Sun:
Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting. KDD 2023: 5393-5403 - [c35]Yifan 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. NeurIPS 2023 - [c34]Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin:
One Fits All: Power General Time Series Analysis by Pretrained LM. NeurIPS 2023 - [i35]Tian Zhou, Peisong Niu, Xue Wang, Liang Sun, Rong Jin:
Power Time Series Forecasting by Pretrained LM. CoRR abs/2302.11939 (2023) - [i34]Qingsong Wen, Linxiao Yang, Liang Sun:
Robust Dominant Periodicity Detection for Time Series with Missing Data. CoRR abs/2303.03553 (2023) - [i33]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. CoRR abs/2303.03640 (2023) - [i32]Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Yi Wang:
DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model. CoRR abs/2306.01001 (2023) - [i31]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 abs/2306.08299 (2023) - [i30]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 abs/2306.08325 (2023) - [i29]Yiyuan Yang, Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection. CoRR abs/2306.10347 (2023) - [i28]Zhixian Wang, Qingsong Wen, Chaoli Zhang, Liang Sun, Leandro Von Krannichfeldt, Yi Wang:
Benchmarks and Custom Package for Electrical Load Forecasting. CoRR abs/2307.07191 (2023) - [i27]Shikai Fang, Qingsong Wen, Shandian Zhe, Liang Sun:
BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition. CoRR abs/2308.14906 (2023) - [i26]Yifan 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 abs/2309.12659 (2023) - [i25]Binqing Wu, Weiqi Chen, Wengwei Wang, Bingqing Peng, Liang Sun, Ling Chen:
WeatherGNN: Exploiting Complicated Relationships in Numerical Weather Prediction Bias Correction. CoRR abs/2310.05517 (2023) - [i24]Linxiao Yang, Rui Ren, Xinyue Gu, Liang Sun:
Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting. CoRR abs/2310.15662 (2023) - [i23]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 abs/2311.14782 (2023) - [i22]Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Liang Sun, Rong Jin:
SVQ: Sparse Vector Quantization for Spatiotemporal Forecasting. CoRR abs/2312.03406 (2023) - [i21]Pengwei Liu, Wenwei Wang, Bingqing Peng, Binqing Wu, Liang Sun:
DSAF: A Dual-Stage Adaptive Framework for Numerical Weather Prediction Downscaling. CoRR abs/2312.12476 (2023) - 2022
- [c33]Yan Li, Rui Xia, Chunchen Liu, Liang Sun:
A Hybrid Causal Structure Learning Algorithm for Mixed-Type Data. AAAI 2022: 7435-7443 - [c32]Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. CIKM 2022: 2497-2507 - [c31]Xiaomin Song, Qingsong Wen, Yan Li, Liang Sun:
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection. CIKM 2022: 4510-4514 - [c30]Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun:
Netrca: An Effective Network Fault Cause Localization Algorithm. ICASSP 2022: 9316-9320 - [c29]Huajie Qian, Qingsong Wen, Liang Sun, Jing Gu, Qiulin Niu, Zhimin Tang:
RobustScaler: QoS-Aware Autoscaling for Complex Workloads. ICDE 2022: 2762-2775 - [c28]Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin:
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. ICML 2022: 27268-27286 - [c27]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: 146-156 - [c26]Qingsong Wen, Linxiao Yang, Tian Zhou, Liang Sun:
Robust Time Series Analysis and Applications: An Industrial Perspective. KDD 2022: 4836-4837 - [c25]Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan:
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. NeurIPS 2022 - [c24]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 - [i20]Tian Zhou, Ziqing Ma, Qingsong Wen, Xue Wang, Liang Sun, Rong Jin:
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting. CoRR abs/2201.12740 (2022) - [i19]Qingsong Wen, Tian Zhou, Chaoli Zhang, Weiqi Chen, Ziqing Ma, Junchi Yan, Liang Sun:
Transformers in Time Series: A Survey. CoRR abs/2202.07125 (2022) - [i18]Chaoli Zhang, Zhiqiang Zhou, Yingying Zhang, Linxiao Yang, Kai He, Qingsong Wen, Liang Sun:
NetRCA: An Effective Network Fault Cause Localization Algorithm. CoRR abs/2202.11269 (2022) - [i17]Huajie Qian, Qingsong Wen, Liang Sun, Jing Gu, Qiulin Niu, Zhimin Tang:
RobustScaler: QoS-Aware Autoscaling for Complex Workloads. CoRR abs/2204.07197 (2022) - [i16]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 abs/2205.08897 (2022) - [i15]Xiaomin Song, Qingsong Wen, Yan Li, Liang Sun:
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection. CoRR abs/2206.02956 (2022) - [i14]Fan Yang, Kai He, Linxiao Yang, Hongxia Du, Jingbang Yang, Bo Yang, Liang Sun:
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach. CoRR abs/2206.03718 (2022) - [i13]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 abs/2206.12106 (2022) - [i12]Chaoli Zhang, Tian Zhou, Qingsong Wen, Liang Sun:
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis. CoRR abs/2210.09693 (2022) - [i11]Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan:
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. CoRR abs/2210.13005 (2022) - 2021
- [c23]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: 4373-4382 - [c22]Qingyang Xu, Qingsong Wen, Liang Sun:
Two-Stage Framework for Seasonal Time Series Forecasting. ICASSP 2021: 3530-3534 - [c21]Linxiao Yang, Qingsong Wen, Bo Yang, Liang Sun:
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition. ICASSP 2021: 5085-5089 - [c20]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: 4653-4660 - [c19]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: 27890-27902 - [c18]Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu:
RobustPeriod: Robust Time-Frequency Mining for Multiple Periodicity Detection. SIGMOD Conference 2021: 2328-2337 - [i10]Qingyang Xu, Qingsong Wen, Liang Sun:
Two-Stage Framework for Seasonal Time Series Forecasting. CoRR abs/2103.02144 (2021) - [i9]Linxiao Yang, Qingsong Wen, Bo Yang, Liang Sun:
A Robust and Efficient Multi-Scale Seasonal-Trend Decomposition. CoRR abs/2109.08800 (2021) - [i8]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 abs/2111.03753 (2021) - 2020
- [c17]Qingsong Wen, Zhengzhi Ma, Liang Sun:
On Robust Variance Filtering and Change of Variance Detection. ICASSP 2020: 3012-3016 - [c16]Qingsong Wen, Zhe Zhang, Yan Li, Liang Sun:
Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns. KDD 2020: 2203-2213 - [i7]Qingsong Wen, Kai He, Liang Sun, Yingying Zhang, Min Ke, Huan Xu:
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicities Detection. CoRR abs/2002.09535 (2020) - [i6]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 abs/2002.09545 (2020) - [i5]Qingsong Wen, Liang Sun, Xiaomin Song, Jingkun Gao, Xue Wang, Huan Xu:
Time Series Data Augmentation for Deep Learning: A Survey. CoRR abs/2002.12478 (2020)
2010 – 2019
- 2019
- [c15]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: 4312-4319 - [c14]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: 5409-5416 - [c13]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: 3856-3862 - [c12]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: 2838-2847 - [i4]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 abs/1901.11149 (2019) - [i3]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 abs/1906.01095 (2019) - [i2]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 abs/1906.03751 (2019) - 2018
- [i1]Qingsong Wen, Jingkun Gao, Xiaomin Song, Liang Sun, Huan Xu, Shenghuo Zhu:
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series. CoRR abs/1812.01767 (2018) - 2011
- [b1]Liang Sun:
Multi-Label Dimensionality Reduction. Arizona State University, Tempe, USA, 2011 - [j4]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): 194-200 (2011) - [c11]Jun Liu, Liang Sun, Jieping Ye:
Projection onto A Nonnegative Max-Heap. NIPS 2011: 487-495 - 2010
- [j3]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): 935-949 (2010) - [c10]Liang Sun, Betul Ceran, Jieping Ye:
A scalable two-stage approach for a class of dimensionality reduction techniques. KDD 2010: 313-322
2000 – 2009
- 2009
- [c9]Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for a class of generalized eigenvalue problems in machine learning. ICML 2009: 977-984 - [c8]Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye:
On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. IJCAI 2009: 1230-1235 - [c7]Zheng Zhao, Liang Sun, Shipeng Yu, Huan Liu, Jieping Ye:
Multiclass Probabilistic Kernel Discriminant Analysis. IJCAI 2009: 1363-1368 - [c6]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: 1335-1344 - [c5]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: 808-816 - [c4]Liang Sun, Jun Liu, Jianhui Chen, Jieping Ye:
Efficient Recovery of Jointly Sparse Vectors. NIPS 2009: 1812-1820 - 2008
- [j2]Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, Jieping Ye:
Automated annotation of Drosophila gene expression patterns using a controlled vocabulary. Bioinform. 24(17): 1881-1888 (2008) - [j1]Liang Sun, Shuiwang Ji, Jieping Ye:
Adaptive diffusion kernel learning from biological networks for protein function prediction. BMC Bioinform. 9 (2008) - [c3]Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for canonical correlation analysis. ICML 2008: 1024-1031 - [c2]Liang Sun, Shuiwang Ji, Jieping Ye:
Hypergraph spectral learning for multi-label classification. KDD 2008: 668-676 - [c1]Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye:
Multi-label Multiple Kernel Learning. NIPS 2008: 777-784
Coauthor Index
[j7] [c55] [c54] [c53] [c52] [c51] [c44] [i46] [i42] [i39] [i36] [j6] [j5] [c43] [c42] [c40] [c39] [c38] [c37] [c35] [i34] [i33] [i32] [i31] [i29] [i28] [i27] [i26] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [i20] [i19] [i18] [i17] [i16] [i15] [i13] [i12] [i11] [c23] [c22] [c21] [c20] [c18] [i10] [i9] [i8] [c17] [c16] [i7] [i6] [i5] [c14] [c13] [i2] [i1]
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