3 papers
cs.LG2024
Effects of Common Regularization Techniques on Open-Set Recognition
Zachary Rabin, Jim Davis, Benjamin Lewis +1
In recent years there has been increasing interest in the field of Open-Set Recognition, which allows a classification model to identify inputs as "unknown" when it encounters an o…
cs.LG2024
Overfitting In Contrastive Learning?
Zachary Rabin, Jim Davis, Benjamin Lewis +1
Overfitting describes a machine learning phenomenon where the model fits too closely to the training data, resulting in poor generalization. While this occurrence is thoroughly doc…
cs.LG2023
Enhancing Self-Training Methods
Aswathnarayan Radhakrishnan, Jim Davis, Zachary Rabin +3
Semi-supervised learning approaches train on small sets of labeled data along with large sets of unlabeled data. Self-training is a semi-supervised teacher-student approach that of…