KI-Glossar
Das vollständige Wörterbuch der Künstlichen Intelligenz
Continual Representation Learning
Process of automatically learning evolving data representations that continuously adapt to new data distributions without requiring explicit labels.
Self-Supervised Continual Learning
Approach where the model generates its own supervision signals from intrinsic data to continuously learn new representations without external labels.
Unsupervised Memory Replay
Technique of storing and reusing previous unlabeled data samples to maintain past knowledge when learning on new data.
Continual Feature Disentanglement
Progressive separation of latent features into interpretable and independent factors while adapting to new unlabeled data distributions.
Task-Agnostic Learning
Learning paradigm where the model is unaware of task boundaries and must continuously adapt to data distribution changes without explicit supervision.
Latent Space Consolidation
Process of stabilizing the latent space to preserve learned structures while allowing the incorporation of new unlabeled representations.
Continual Unsupervised Feature Discovery
Ability of a system to continuously identify and extract new relevant features from unlabeled data streams.
Experience Replay without Labels
Strategy of memorizing and reusing past experiences based solely on intrinsic data structures rather than supervision labels.
Continual Unsupervised Domain Adaptation
Progressive and automatic adaptation of a model to new data domains without labels, while preserving performance on previous domains.
Continual Representation Alignment
Technique aimed at maintaining the consistency of learned representations across different phases of unsupervised learning to avoid conceptual drift.
Neural Plasticity Control
Mechanisms regulating the degree of adaptability of neural weights to balance learning new information and preserving existing knowledge.
Contrastive Continual Learning
Approach based on contrastive learning applied continuously to discover and maintain discriminative representations without labels.
Knowledge Preservation without Supervision
Set of techniques allowing preservation of knowledge acquired during continual learning in the complete absence of external supervision signals.
Unsupervised Elastic Weight Consolidation
Adaptation of the EWC method to unsupervised context, identifying important weights for past tasks without requiring explicit labels.