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Found 6 papers, 0 papers with code
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
A simple neural network then learns the implicit mapping from the intra- and inter-sample relations to an adaptive, sample-wise knowledge fusion ratio in a bilevel-optimization manner.
Teacher-Student Architecture for Knowledge Distillation: A Survey
Recently, Teacher-Student architectures have been effectively and widely embraced on various knowledge distillation (KD) objectives, including knowledge compression, knowledge expansion, knowledge adaptation, and knowledge enhancement.
Phase Matching for Out-of-Distribution Generalization
In this paper, we aim to clarify the relationships between Domain Generalization (DG) and the frequency components, and explore the spatial relationships of the phase spectrum.
Teacher-Student Architecture for Knowledge Learning: A Survey
To tackle this issue, Teacher-Student architectures were first utilized in knowledge distillation, where simple student networks can achieve comparable performance to deep teacher networks.
Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Survey
However, the temporal information embedded in the dynamic graphs brings new challenges in analyzing and deploying them.
MOBA: Multi-teacher Model Based Reinforcement Learning
Results show that, compared with SOTA model-free methods, our method can improve the data efficiency and system performance by up to 75% and 10%, respectively.
