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cs.LG2026★ 1 cited
Inhibitor Transformers and Gated RNNs for Torus Efficient Fully Homomorphic Encryption
Rickard Brännvall, Tony Zhang, Henrik Forsgren +3
This paper introduces efficient modifications to neural network-based sequence processing approaches, laying new grounds for scalable privacy-preserving machine learning under Full…
cs.LG2024
Sharing to learn and learning to share; Fitting together Meta-Learning, Multi-Task Learning, and Transfer Learning: A meta review
Richa Upadhyay, Ronald Phlypo, Rajkumar Saini +1
Integrating knowledge across different domains is an essential feature of human learning. Learning paradigms such as transfer learning, meta-learning, and multi-task learning refle…