7 citations · 21 across the 23 of their papers we have counts for
4 papers · 1 filter
Automatic Generation of Multi-precision Multi-arithmetic CNN Accelerators for FPGAs
Yiren Zhao, Xitong Gao, Xuan Guo +6
Modern deep Convolutional Neural Networks (CNNs) are computationally demanding, yet real applications often require high throughput and low latency. To help tackle these problems,…
Blackbox Attacks on Reinforcement Learning Agents Using Approximated Temporal Information
Yiren Zhao, Ilia Shumailov, Han Cui +3
Recent research on reinforcement learning (RL) has suggested that trained agents are vulnerable to maliciously crafted adversarial samples. In this work, we show how such samples c…
Focused Quantization for Sparse CNNs
Yiren Zhao, Xitong Gao, Daniel Bates +2
Deep convolutional neural networks (CNNs) are powerful tools for a wide range of vision tasks, but the enormous amount of memory and compute resources required by CNNs pose a chall…
Sitatapatra: Blocking the Transfer of Adversarial Samples
Ilia Shumailov, Xitong Gao, Yiren Zhao +3
Convolutional Neural Networks (CNNs) are widely used to solve classification tasks in computer vision. However, they can be tricked into misclassifying specially crafted `adversari…