Jun 24, 2019 · In this paper, we study a deep-model reusing task, where we are given as input pre-trained networks of heterogeneous architectures specializing in distinct ...

The knowledge amalgamation is achieved by learning a common feature space, in which the studen- t is encouraged to imitate the teachers' features. We apply.

Official implementation of Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning (IJCAI 2019) in pytorch.

This paper proposes a common feature learning scheme, in which the features of all teachers are transformed into a common space and the student is enforced ...

In this paper, we study a deep-model reusing task, where we are given as input pre-trained networks of heterogeneous architectures specializing in distinct ...

Jun 24, 2019 · In this paper, we study a deep-model reusing task, where we are given as input pre-trained networks of heterogeneous architectures specializing ...

Aug 10, 2019 · In this paper, we study a deep-model reusing task, where we are given as input pre-trained networks of heterogeneous architectures specializing ...

@inproceedings{ijcai2019p428, title = {Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning}, author = {Luo, Sihui and Wang ...

KAmalEngine (KAE) aims at building a lightweight algorithm package for Knowledge Amalgamation, Knowledge Distillation and Model Transferability Estimation.

Jun 24, 2019 · Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning. Sihui Luo1 , Xinchao Wang2 , Gongfan Fang1 , Yao Hu3 , Dapeng ...