167 citations · 495 across the 52 of their papers we have counts for
14 papers · 1 filter
ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks
Xiaodan Hu, Audrey G. Chung, Paul Fieguth +3
Generative Adversarial Networks (GANs) have shown considerable promise for mitigating the challenge of data scarcity when building machine learning-driven analysis algorithms. Spec…
Mitigating Architectural Mismatch During the Evolutionary Synthesis of Deep Neural Networks
Audrey Chung, Paul Fieguth, Alexander Wong
Evolutionary deep intelligence has recently shown great promise for producing small, powerful deep neural network models via the organic synthesis of increasingly efficient archite…
EdgeSpeechNets: Highly Efficient Deep Neural Networks for Speech Recognition on the Edge
Zhong Qiu Lin, Audrey G. Chung, Alexander Wong
Despite showing state-of-the-art performance, deep learning for speech recognition remains challenging to deploy in on-device edge scenarios such as mobile and other consumer devic…
PolyNeuron: Automatic Neuron Discovery via Learned Polyharmonic Spline Activations
Andrew Hryniowski, Alexander Wong
Automated deep neural network architecture design has received a significant amount of recent attention. However, this attention has not been equally shared by one of the fundament…
SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections
Amir-Hossein Karimi, Alexander Wong, Ali Ghodsi
Supervised dimensionality reduction strategies have been of great interest. However, current supervised dimensionality reduction approaches are difficult to scale for situations ch…
Dynamic Representations Toward Efficient Inference on Deep Neural Networks by Decision Gates
Mohammad Saeed Shafiee, Mohammad Javad Shafiee, Alexander Wong
While deep neural networks extract rich features from the input data, the current trade-off between depth and computational cost makes it difficult to adopt deep neural networks fo…