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Found 4 papers, 2 papers with code
CRISP: Hybrid Structured Sparsity for Class-aware Model Pruning
Machine learning pipelines for classification tasks often train a universal model to achieve accuracy across a broad range of classes.
Visual-Policy Learning through Multi-Camera View to Single-Camera View Knowledge Distillation for Robot Manipulation Tasks
Our proposed method involves utilizing a technique known as knowledge distillation, in which a pre-trained ``teacher'' policy trained with multiple camera viewpoints guides a ``student'' policy in learning from a single camera viewpoint.
Robust and Resource-Efficient Data-Free Knowledge Distillation by Generative Pseudo Replay
In particular, we design a Variational Autoencoder (VAE) with a training objective that is customized to learn the synthetic data representations optimally.
Preventing Catastrophic Forgetting and Distribution Mismatch in Knowledge Distillation via Synthetic Data
Moreover, the sample generation strategies in some of these methods could result in a mismatch between the synthetic and real data distributions.
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