6.5k citations · 10.4k across the 118 of their papers we have counts for
14 papers · 1 filter
Trust Region Based Adversarial Attack on Neural Networks
Zhewei Yao, Amir Gholami, Peng Xu +2
Deep Neural Networks are quite vulnerable to adversarial perturbations. Current state-of-the-art adversarial attack methods typically require very time consuming hyper-parameter tu…
Parameter Re-Initialization through Cyclical Batch Size Schedules
Norman Mu, Zhewei Yao, Amir Gholami +2
Optimal parameter initialization remains a crucial problem for neural network training. A poor weight initialization may take longer to train and/or converge to sub-optimal solutio…
FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search
Bichen Wu, Xiaoliang Dai, Peizhao Zhang +7
Designing accurate and efficient ConvNets for mobile devices is challenging because the design space is combinatorially large. Due to this, previous neural architecture search (NAS…
Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search
Bichen Wu, Yanghan Wang, Peizhao Zhang +3
Recent work in network quantization has substantially reduced the time and space complexity of neural network inference, enabling their deployment on embedded and mobile devices wi…
Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs
Yifan Yang, Qijing Huang, Bichen Wu +8
Using FPGAs to accelerate ConvNets has attracted significant attention in recent years. However, FPGA accelerator design has not leveraged the latest progress of ConvNets. As a res…
A Novel Domain Adaptation Framework for Medical Image Segmentation
Amir Gholami, Shashank Subramanian, Varun Shenoy +6
We propose a segmentation framework that uses deep neural networks and introduce two innovations. First, we describe a biophysics-based domain adaptation method. Second, we propose…