39 citations · 123 across the 13 of their papers we have counts for
8 papers · 1 filter
Width Transfer: On the (In)variance of Width Optimization
Ting-Wu Chin, Diana Marculescu, Ari S. Morcos
Optimizing the channel counts for different layers of a CNN has shown great promise in improving the efficiency of CNNs at test-time. However, these methods often introduce large c…
FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference
Ruizhou Ding, Zeye Liu, Ting-Wu Chin +3
To improve the throughput and energy efficiency of Deep Neural Networks (DNNs) on customized hardware, lightweight neural networks constrain the weights of DNNs to be a limited com…
Regularizing Activation Distribution for Training Binarized Deep Networks
Ruizhou Ding, Ting-Wu Chin, Zeye Liu +1
Binarized Neural Networks (BNNs) can significantly reduce the inference latency and energy consumption in resource-constrained devices due to their pure-logical computation and few…
Towards Efficient Model Compression via Learned Global Ranking
Ting-Wu Chin, Ruizhou Ding, Cha Zhang +1
Pruning convolutional filters has demonstrated its effectiveness in compressing ConvNets. Prior art in filter pruning requires users to specify a target model complexity (e.g., mod…
AdaScale: Towards Real-time Video Object Detection Using Adaptive Scaling
Ting-Wu Chin, Ruizhou Ding, Diana Marculescu
In vision-enabled autonomous systems such as robots and autonomous cars, video object detection plays a crucial role, and both its speed and accuracy are important factors to provi…
Understanding the Impact of Label Granularity on CNN-based Image Classification
Zhuo Chen, Ruizhou Ding, Ting-Wu Chin +1
In recent years, supervised learning using Convolutional Neural Networks (CNNs) has achieved great success in image classification tasks, and large scale labeled datasets have cont…
Layer-compensated Pruning for Resource-constrained Convolutional Neural Networks
Ting-Wu Chin, Cha Zhang, Diana Marculescu
Resource-efficient convolution neural networks enable not only the intelligence on edge devices but also opportunities in system-level optimization such as scheduling. In this work…
Domain Specific Approximation for Object Detection
Ting-Wu Chin, Chia-Lin Yu, Matthew Halpern +3
There is growing interest in object detection in advanced driver assistance systems and autonomous robots and vehicles. To enable such innovative systems, we need faster object det…