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Found 3 papers, 2 papers with code
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection
Recent studies on learning with noisy labels have shown remarkable performance by exploiting a small clean dataset.
Efficient Click-Through Rate Prediction for Developing Countries via Tabular Learning
Despite the rapid growth of online advertisement in developing countries, existing highly over-parameterized Click-Through Rate (CTR) prediction models are difficult to be deployed due to the limited computing resources.
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
Among many approaches, the simplest and most intuitive way is zero imputation, which treats the value of a missing entry simply as zero.
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