Abstract: The analysis of transaction data is often impeded by challenges such as noise, inconsistencies, high dimensionality, and missing values, which obscure valuable insights. Existing ...
Abstract: In the era of pervasive computing, machine learning (ML) is increasingly deployed on resource-constrained devices, such as smartphones, IoT devices, and edge nodes. This research explores ML ...
Overview: Poor data validation, leakage, and weak preprocessing pipelines cause most XGBoost and LightGBM model failures in production.Default hyperparameters, ...
We present TrackNetV3, a model composed of two core modules: trajectory prediction and rectification. The trajectory prediction module leverages an estimated background as auxiliary data to locate the ...
We present TrackNetV3, a model composed of two core modules: trajectory prediction and rectification. The trajectory prediction module leverages an estimated background as auxiliary data to locate the ...
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