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Found 3 papers, 1 papers with code
Teacher Network Calibration Improves Cross-Quality Knowledge Distillation
We investigate cross-quality knowledge distillation (CQKD), a knowledge distillation method where knowledge from a teacher network trained with full-resolution images is transferred to a student network that takes as input low-resolution images.
Demand Forecasting using Long Short-Term Memory Neural Networks
In this paper we investigate to what extent long short-term memory neural networks (LSTMs) are suitable for demand forecasting in the e-grocery retail sector.
Rectifying Classifier Chains for Multi-Label Classification
Classifier chains have recently been proposed as an appealing method for tackling the multi-label classification task.
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