3 papers
cs.CV2024
SAFT: Towards Out-of-Distribution Generalization in Fine-Tuning
Bac Nguyen, Stefan Uhlich, Fabien Cardinaux +3
Handling distribution shifts from training data, known as out-of-distribution (OOD) generalization, poses a significant challenge in the field of machine learning. While a pre-trai…
cs.LG2023
DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation
Pau Mulet Arabi, Alec Flowers, Lukas Mauch +1
Computing gradients of an expectation with respect to the distributional parameters of a discrete distribution is a problem arising in many fields of science and engineering. Typic…
cs.SD2023
Improving Self-Supervised Learning for Audio Representations by Feature Diversity and Decorrelation
Bac Nguyen, Stefan Uhlich, Fabien Cardinaux
Self-supervised learning (SSL) has recently shown remarkable results in closing the gap between supervised and unsupervised learning. The idea is to learn robust features that are…