scalable learning
Scalable learning refers to the capability of machine learning algorithms to effectively handle increasing amounts of data or complexity without significant loss of performance. This is important for deploying AI systems in real-world applications with large datasets.
- Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning
- FORLA: Federated Object-centric Representation Learning with Slot Attention
- Few-Shot Learning from Gigapixel Images via Hierarchical Vision-Language Alignment and Modeling
- Neurosymbolic Diffusion Models
- Revisiting Semi-Supervised Learning in the Era of Foundation Models