Revisiting k-nearest neighbor benchmarks in self-supervised learning
Standard protocols for benchmarking self-supervised models involve using a linear or k-nearest neighbor classification on frozen features of the learned model. However, both evaluations are sensitive to hyperparameters making the evaluation and comparison complicated. Read more