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Xi Liu
Also published under:
Affiliation
Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA
Topic
Ensemble Model,Multi-task Learning,Root Mean Square Error,Spatiotemporal Data,Time Series,Average Mean Absolute Error,Baseline Methods,Batch Learning,Build Regression Models,Data Framework,Dynamical,Efficient Model,Ensemble Forecasts,Ensemble Members,Error Distribution,Feed-forward Network,Gaussian Kernel Density Estimation,Global Historical Climatology Network,Global Model,Gradient Descent,Gradient Descent Approach,Grid Cells,Heavy-tailed,Hierarchical Framework,Hierarchical Long Short-term Memory,Hyperparameters,Incremental Learning,Incremental Update,Latent Factors,Lead Time,Limited Training Data,Long Short-term Memory,Long Short-term Memory Framework,Long Short-term Memory Network,Long-term Forecasting,Long-term Prediction,Loss Function,Mini-batch Gradient Descent,Model Parameters,Monthly Sea Surface Temperature,Multi-model Ensemble,Multi-step Prediction,Multi-task Regression,Multilevel Structure,Nested Cross-validation,Nonparametric Density Estimation,North Atlantic Oscillation,Objective Function,Observational Data,Over Space,
Biography
Xi Liu received the bachelor's degree from the Electronics and Communications Engineering Department, Xi'an Jiaotong University, in 2011. She is currently working toward the PhD degree in the Department of Computer Science and Engineering, Michigan State University. Her research focuses on data mining and machine learning techniques on sensing data. One of her works received the 1st place winner in Discovery Challenge of ECML-PKDD’2016.