Trinidad and Tobago
AThe
B.2.1 Metrics Theevaluationmetricsweuseare Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE).
Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.72)
Task-oriented Time Series Imputation Evaluation via Generalized Representers Zhixian Wang 1,2, Linxiao Y ang
Specifically, we summarize our contributions into the following points.
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- Asia > South Korea > Seoul > Seoul (0.04)
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- North America > Trinidad and Tobago > Trinidad > Arima > Arima (0.04)
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Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking Xi Chen
To bridge this gap, we present Job-SDF, a dataset designed to train and benchmark job-skill demand forecasting models.
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- North America > Trinidad and Tobago > Trinidad > Arima > Arima (0.04)
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- Health & Medicine > Therapeutic Area (1.00)
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AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
By introducing LLM-embedded textual timestamps, Auto-Times can utilize chronological information to align multivariate time series. Empirically, AutoTimes achieves state-of-the-art with 0.1% trainable parameters and
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- North America > Trinidad and Tobago > Trinidad > Arima > Arima (0.04)
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- Energy (0.68)
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- Oceania > Australia > New South Wales (0.04)
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- Research Report > Experimental Study (0.93)
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