212 citations · 316 across the 8 of their papers we have counts for
12 papers
Optimal Quantization for Batch Normalization in Neural Network Deployments and Beyond
Dachao Lin, Peiqin Sun, Guangzeng Xie +2
Quantized Neural Networks (QNNs) use low bit-width fixed-point numbers for representing weight parameters and activations, and are often used in real-world applications due to thei…
Are L2 adversarial examples intrinsically different?
Mingxuan Li, Jingyuan Wang, Yufan Wu
Deep Neural Network (DDN) has achieved notable success in various tasks, including many security concerning scenarios. However, a considerable amount of work has proved its vulnera…
Learning to Paint With Model-based Deep Reinforcement Learning
Zhewei Huang, Wen Heng, Shuchang Zhou
We show how to teach machines to paint like human painters, who can use a small number of strokes to create fantastic paintings. By employing a neural renderer in model-based Deep…
Harmonic Adversarial Attack Method
Wen Heng, Shuchang Zhou, Tingting Jiang
Adversarial attacks find perturbations that can fool models into misclassifying images. Previous works had successes in generating noisy/edge-rich adversarial perturbations, at the…
Stroke-based Character Reconstruction
Zhewei Huang, Wen Heng, Yuanzheng Tao +1
Background elimination for noisy character images or character images from real scene is still a challenging problem, due to the bewildering backgrounds, uneven illumination, low r…
Interpolatron: Interpolation or Extrapolation Schemes to Accelerate Optimization for Deep Neural Networks
Guangzeng Xie, Yitan Wang, Shuchang Zhou +1
In this paper we explore acceleration techniques for large scale nonconvex optimization problems with special focuses on deep neural networks. The extrapolation scheme is a classic…