Abstract: Hyperparameter tuning is a crucial process in the machine learning (ML) pipeline, as the performance of a learning algorithm is highly influenced by its hyperparameter configuration. This ...

According to @godofprompt, a widespread trend in artificial intelligence research involves systematic p-hacking, where experiments are repeatedly run until benchmarks show improvement, with successes ...

Sometimes we assume the people and things around us are neutral or hostile to our existence. What if the opposite could be true? By Melissa Kirsch Normally I pass my morning commute absorbed in a book ...

Hyperparameter tuning is critical to the success of cross-device federated learning applications. Unfortunately, federated networks face issues of scale, heterogeneity, and privacy; addressing these ...

Spearmint integrated Bayesian Optimization for hyper parameter tuning of Auto sparse encoder embedded with softmax Classifier for MNIST digit Classification. Platform + GUI for hyperparameter ...

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.