5 citations · 5 across the 3 of their papers we have counts for
3 papers
Towards Composable Distributions of Latent Space Augmentations
Omead Pooladzandi, Jeffrey Jiang, Sunay Bhat +1
We propose a composable framework for latent space image augmentation that allows for easy combination of multiple augmentations. Image augmentation has been shown to be an effecti…
Generating High Fidelity Synthetic Data via Coreset selection and Entropic Regularization
Omead Pooladzandi, Pasha Khosravi, Erik Nijkamp +1
Generative models have the ability to synthesize data points drawn from the data distribution, however, not all generated samples are high quality. In this paper, we propose using…
Adaptive Second Order Coresets for Data-efficient Machine Learning
Omead Pooladzandi, David Davini, Baharan Mirzasoleiman
Training machine learning models on massive datasets incurs substantial computational costs. To alleviate such costs, there has been a sustained effort to develop data-efficient tr…