Graph Neural Networks (GNNs) have emerged as a powerful category of lear...
Style transfer aims to render the style of a given image for style refer...
In this paper, we study a novel task that enables partial knowledge tran...
In this paper, we study \xw{dataset distillation (DD)}, from a novel
per...
Neural networks (NNs) and decision trees (DTs) are both popular models o...
Life-long learning aims at learning a sequence of tasks without forgetti...
One key challenge of exemplar-guided image generation lies in establishi...
In this paper, we explore a novel and ambitious knowledge-transfer task,...
Knowledge distillation (KD) has become a well established paradigm for
c...
Knowledge distillation (KD) has recently emerged as a powerful strategy ...
Existing state-of-the-art human pose estimation methods require heavy
co...
Recent advances in deep learning have provided procedures for learning o...
Exploring the intrinsic interconnections between the knowledge encoded i...
Many well-trained Convolutional Neural Network(CNN) models have now been...
In this paper, we investigate a novel deep-model reusing task. Our goal ...
The recent work of Gatys et al. demonstrated the power of Convolutional
...