44 citations · 244 across the 30 of their papers we have counts for
5 papers · 1 filter
Learning Sparse Mixture of Experts for Visual Question Answering
Vardaan Pahuja, Jie Fu, Christopher J. Pal
There has been a rapid progress in the task of Visual Question Answering with improved model architectures. Unfortunately, these models are usually computationally intensive due to…
Conditional Computation for Continual Learning
Min Lin, Jie Fu, Yoshua Bengio
Catastrophic forgetting of connectionist neural networks is caused by the global sharing of parameters among all training examples. In this study, we analyze parameter sharing unde…
Structure Learning for Neural Module Networks
Vardaan Pahuja, Jie Fu, Sarath Chandar +1
Neural Module Networks, originally proposed for the task of visual question answering, are a class of neural network architectures that involve human-specified neural modules, each…
Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning
Dayiheng Liu, Jie Fu, Yidan Zhang +2
Typical methods for unsupervised text style transfer often rely on two key ingredients: 1) seeking the explicit disentanglement of the content and the attributes, and 2) troublesom…
Dataflow-based Joint Quantization of Weights and Activations for Deep Neural Networks
Xue Geng, Jie Fu, Bin Zhao +4
This paper addresses a challenging problem - how to reduce energy consumption without incurring performance drop when deploying deep neural networks (DNNs) at the inference stage.…