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We stand with Ukraine

Shun Zheng

Orcid: 0009-0008-6071-5960

According to our database¹, Shun Zheng authored at least 30 papers between 2012 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

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PhD thesis

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Links

On csauthors.net:

Bibliography

2024

DEWP: Deep Expansion Learning for Wind Power Forecasting.

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ACM Trans. Knowl. Discov. Data, April, 2024

Large Language Model as a Universal Clinical Multi-task Decoder.

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CoRR, 2024

Addressing Distribution Shift in Time Series Forecasting with Instance Normalization Flows.

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CoRR, 2024

From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models.

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Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

BatteryML: An Open-source Platform for Machine Learning on Battery Degradation.

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Proceedings of the Twelfth International Conference on Learning Representations, 2024

PTaRL: Prototype-based Tabular Representation Learning via Space Calibration.

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Xiaozhuang Song

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Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

BatteryML: An Open-source platform for Machine Learning on Battery Degradation.

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CoRR, 2023

ProbTS: A Unified Toolkit to Probe Deep Time-series Forecasting.

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CoRR, 2023

Towards Foundation Models for Learning on Tabular Data.

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CoRR, 2023

Learning Intra- and Inter-Cell Differences for Accurate Battery Lifespan Prediction across Diverse Conditions.

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CoRR, 2023

Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series.

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Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

UADB: Unsupervised Anomaly Detection Booster.

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Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Multi-pair Contrastive Learning Based on Same-Timestamp Data Augmentation for Sequential Recommendation.

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Proceedings of the Web and Big Data - 7th International Joint Conference, 2023

Efficient Graph Collaborative Filtering with Multi-layer Output-Enhanced Contrastive Learning.

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Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

2022

Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures.

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CoRR, 2022

Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations.

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Xiaozhuang Song

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Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Differential Operators for Interpretable Time Series Modeling.

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Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting.

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Proceedings of the Tenth International Conference on Learning Representations, 2022

A Graph-based Spatiotemporal Model for Energy Markets.

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Srinivasan Iyengar

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Shivkumar Kalyanaraman

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Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

A continuous glucose monitoring measurements forecasting approach via sporadic blood glucose monitoring.

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Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2022

2021

The CityLearn Challenge 2022: Overview, Results, and Lessons Learned.

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Proceedings of the NeurIPS 2022 Competition Track, 2021

HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting.

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Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Revisiting the Evaluation of End-to-end Event Extraction.

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Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

SEEK: Segmented Embedding of Knowledge Graphs.

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Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction.

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Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

DIAG-NRE: A Neural Pattern Diagnosis Framework for Distantly Supervised Neural Relation Extraction.

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Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

DIAG-NRE: A Deep Pattern Diagnosis Framework for Distant Supervision Neural Relation Extraction.

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CoRR, 2018

2017

A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization.

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J. Mach. Learn. Res., 2017

2016

A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization.

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CoRR, 2016

2012

Label-Free Electrochemical Diagnosis of Viral Antigens with Genetically Engineered Fusion Protein.

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Sensors, 2012

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