Aug 26, 2019 · Specifically, we propose "stochastic filter groups'' (SFG), a mechanism to assign convolution kernels in each layer to "specialist'' or " ...

Abstract. The performance of multi-task learning in Convolutional. Neural Networks (CNNs) hinges on the design of feature sharing between tasks within the ...

Specifically, we propose "stochastic filter groups" (SFG), a mechanism to assign convolution kernels in each layer to "specialist" and "generalist" groups, ...

Specifically, we propose "stochastic filter groups" (SFG), a mechanism to assign convolution kernels in each layer to "specialist" and "generalist" groups, ...

This paper proposes "stochastic filter groups" (SFG), a mechanism to assign convolution kernels in each layer to "specialist" and "generalist" groups, ...

Stochastic Filter Groups for Multi-Task. CNNs: Learning Specialist and. Generalist Convolution Kernels ... • The benefits of multi-task learning (MTL) depend ...

Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels. Felix J.S. Bragman⇤. University College London, UK f ...

Aug 29, 2019 · In this paper, we present a probabilistic approach to learning task-specific and shared representations in CNNs for multi-task learning.

Stochastic Filter Groups for Multi-Task CNNs ... • Core idea: cluster convolution kernels into task specific and shared groups in each layer of a CNN.

Supplementary material: Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels. Felix J.S. Bragman∗. University ...