Rolling Ball Optimizer: Learning by ironing out loss landscape wrinkles

arXiv — cs.LG•Monday, October 27, 2025 at 4:00:00 AM

The Rolling Ball Optimizer is a groundbreaking approach to training large neural networks by addressing the complexities of loss landscapes. These landscapes can be filled with tricky local minima and other challenges that make optimization difficult. By 'ironing out' these wrinkles, this method enhances the efficiency of training, potentially leading to better-performing models. This innovation is significant as it could streamline the training process for AI systems, making them more effective and reliable in various applications.

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