François Fleuret

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

2020 · Infoscience (Ecole Polytechnique Fédérale de Lausanne)

The performance of optimizers, particularly in deep learning, depends considerably on their chosen hyperparameter configuration. The efficacy of optimizers is often studied under near-optimal problem-specific hyperparameters, and finding these settings may be prohibitively costly for …

Computing Preimages of Deep Neural Networks with Applications to Safety

2021

To apply an algorithm in a sensitive domain it is important to understand the set of input values that result in specific decisions. Deep neural networks suffer from an inherent instability that makes this difficult: …