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Found 5 papers, 2 papers with code
Efficient Pointwise-Pairwise Learning-to-Rank for News Recommendation
Extensive experiments show that our approach outperforms the state-of-the-art methods on the MIND and Adressa news recommendation datasets.
Automatic Termination for Hyperparameter Optimization
Across an extensive range of real-world HPO problems and baselines, we show that our termination criterion achieves a better trade-off between the test performance and optimization time.
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization
To democratize access to machine learning systems, it is essential to automate the tuning.
Amazon SageMaker Autopilot: a white box AutoML solution at scale
AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of the entire pipeline.
Chargrid: Towards Understanding 2D Documents
We introduce a novel type of text representation that preserves the 2D layout of a document.
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