all AI news
CoViews: Adaptive Augmentation Using Cooperative Views for Enhanced Contrastive Learning
May 14, 2024, 4:46 a.m. | Nazim Bendib
cs.CV updates on arXiv.org arxiv.org
Abstract: Data augmentation plays a critical role in generating high-quality positive and negative pairs necessary for effective contrastive learning. However, common practices involve using a single augmentation policy repeatedly to generate multiple views, potentially leading to inefficient training pairs due to a lack of cooperation between views. Furthermore, to find the optimal set of augmentations, many existing methods require extensive supervised evaluation, overlooking the evolving nature of the model that may require different augmentations throughout the …
abstract arxiv augmentation cs.cv data generate however multiple negative policy positive practices quality role training type
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
Software Engineer III -Full Stack Developer - ModelOps, MLOps
@ JPMorgan Chase & Co. | NY, United States
Senior Lead Software Engineer - Full Stack Senior Developer - ModelOps, MLOps
@ JPMorgan Chase & Co. | NY, United States
Software Engineer III - Full Stack Developer - ModelOps, MLOps
@ JPMorgan Chase & Co. | NY, United States
Research Scientist (m/w/d) - Numerische Simulation Laser-Materie-Wechselwirkung
@ Fraunhofer-Gesellschaft | Freiburg, DE, 79104
Research Scientist, Speech Real-Time Dialog
@ Google | Mountain View, CA, USA