This AI Research Addresses the Problem of ‘Loss of Plasticity’ in Deep Learning Systems When Used in Continual Learning Settings

Modern deep-learning algorithms are now focused on problem environments where training occurs just once on a sizable data collection, never again—all of the early triumphs of deep learning in voice recognition and picture classification employed such train-once settings. Replay buffers and batching were later added to deep understanding when applied to reinforcement learning, making it […]

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