Hao Huang
Affiliations:- GE Global Research, San Ramon, CA, USA
- Stony Brook University, Department of Computer Science, Stony Brook, NY, USA
According to our database1,
Hao Huang
authored at least 31 papers
between 2011 and 2024.
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Bibliography
2024
Deep Root Cause Analysis: Unveiling Anomalies and Enhancing Fault Detection in Industrial Time Series.
Proceedings of the International Joint Conference on Neural Networks, 2024
Proceedings of the Pattern Recognition - 27th International Conference, 2024
Energy Efficient Streaming Time Series Classification with Attentive Power Iteration.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023
2022
Proceedings of the IEEE International Conference on Big Data, 2022
2021
Interpretable temporal GANs for industrial imbalanced multivariate time series simulation and classification.
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021
Proceedings of the SAC '21: The 36th ACM/SIGAPP Symposium on Applied Computing, 2021
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021
A Deep Neural Network for Multivariate Time Series Clustering with Result Interpretation.
Proceedings of the International Joint Conference on Neural Networks, 2021
Learning Associations between Features and Clusters: An Interpretable Deep Clustering Method.
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
Imbalanced Time Series Classification for Flight Data Analyzing with Nonlinear Granger Causality Learning.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020
2019
Redundant features removal for unsupervised spectral feature selection algorithms: an empirical study based on nonparametric sparse feature graph.
Int. J. Data Sci. Anal., 2019
Failure Analysis on Multivariate Time-series Data given Uncertain Labels.
Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2019
Bi-directional Causal Graph Learning through Weight-Sharing and Low-Rank Neural Network.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019
2017
Automatically Redundant Features Removal for Unsupervised Feature Selection via Sparse Feature Graph.
CoRR, 2017
2016
IEEE Trans. Knowl. Data Eng., 2016
Proceedings of the 32nd IEEE International Conference on Data Engineering, 2016
2015
ACM Trans. Knowl. Discov. Data, 2015
Proceedings of the 30th Annual ACM Symposium on Applied Computing, 2015
A Stochastic Framework for Solar Irradiance Forecasting Using Condition Random Field.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015
2014
ACM Trans. Knowl. Discov. Data, 2014
Diffusion-based clustering analysis of coherent X-ray scattering patterns of self-assembled nanoparticles.
Proceedings of the Symposium on Applied Computing, 2014
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
Proceedings of the 2014 IEEE International Conference on Data Mining, 2014
2013
Proceedings of the IEEE Fourth International Conference on Smart Grid Communications, 2013
2012
Proceedings of the 12th IEEE International Conference on Data Mining, 2012
Local anomaly descriptor: a robust unsupervised algorithm for anomaly detection based on diffusion space.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012
2011
Proceedings of the 11th IEEE International Conference on Data Mining, 2011