Download to read offline
Uploaded byKazuyuki Tokuyama
300 views
Facebook活用ワークショップセミナー20110827
The document discusses a new approach to machine learning that trains models on unlabeled data using self-supervision, allowing the models to learn useful representations of the data without human labels. This technique involves predicting missing or corrupted parts of the input and can be applied to a wide range of tasks like vision, language, and reinforcement learning. Researchers have found that models trained this way learn representations that are useful for downstream supervised learning tasks.
