Liang Sun
Orcid: 0009-0002-5835-7259Affiliations:
- Alibaba Group, Bellevue, WA, USA
- Arizona State University, Tempe, AZ, USA (former)
According to our database1,
Liang Sun
authored at least 68 papers
between 2008 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
CoRR, 2024
Sparse-VQ Transformer: An FFN-Free Framework with Vector Quantization for Enhanced Time Series Forecasting.
CoRR, 2024
FusionSF: Fuse Heterogeneous Modalities in a Vector Quantized Framework for Robust Solar Power Forecasting.
CoRR, 2024
2023
Energy forecasting with robust, flexible, and explainable machine learning algorithms.
AI Mag., December, 2023
Personalized Federated DARTS for Electricity Load Forecasting of Individual Buildings.
IEEE Trans. Smart Grid, November, 2023
CoRR, 2023
One Fits All: Universal Time Series Analysis by Pretrained LM and Specially Designed Adaptors.
CoRR, 2023
WeatherGNN: Exploiting Complicated Relationships in Numerical Weather Prediction Bias Correction.
CoRR, 2023
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling.
CoRR, 2023
BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition.
CoRR, 2023
GCformer: An Efficient Framework for Accurate and Scalable Long-Term Multivariate Time Series Forecasting.
CoRR, 2023
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Interactive Generalized Additive Model and Its Applications in Electric Load Forecasting.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
SADI: A Self-Adaptive Decomposed Interpretable Framework for Electric Load Forecasting Under Extreme Events.
Proceedings of the IEEE International Conference on Acoustics, 2023
GCformer: An Efficient Solution for Accurate and Scalable Long-Term Multivariate Time Series Forecasting.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the IEEE International Conference on Acoustics, 2021
Proceedings of the IEEE International Conference on Acoustics, 2021
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021
2020
RobustTAD: Robust Time Series Anomaly Detection via Decomposition and Convolutional Neural Networks.
CoRR, 2020
CoRR, 2020
Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
2019
Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2011
Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis.
IEEE Trans. Pattern Anal. Mach. Intell., 2011
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011
2010
Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation.
NeuroImage, 2010
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010
2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Mining brain region connectivity for alzheimer's disease study via sparse inverse covariance estimation.
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009
Proceedings of the IJCAI 2009, 2009
On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares.
Proceedings of the IJCAI 2009, 2009
A least squares formulation for a class of generalized eigenvalue problems in machine learning.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
2008
Adaptive diffusion kernel learning from biological networks for protein function prediction.
BMC Bioinform., 2008
Automated annotation of <i>Drosophila</i> gene expression patterns using a controlled vocabulary.
Bioinform., 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008
Proceedings of the Machine Learning, 2008