108 citations · 190 across the 6 of their papers we have counts for
6 papers
LiBRe: A Practical Bayesian Approach to Adversarial Detection
Zhijie Deng, Xiao Yang, Shizhen Xu +2
Despite their appealing flexibility, deep neural networks (DNNs) are vulnerable against adversarial examples. Various adversarial defense strategies have been proposed to resolve t…
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Zhaocheng Zhu, Shizhen Xu, Meng Qu +1
Learning continuous representations of nodes is attracting growing interest in both academia and industry recently, due to their simplicity and effectiveness in a variety of applic…
Fast Locality Sensitive Hashing for Beam Search on GPU
Xing Shi, Shizhen Xu, Kevin Knight
We present a GPU-based Locality Sensitive Hashing (LSH) algorithm to speed up beam search for sequence models. We utilize the winner-take-all (WTA) hash, which is based on relative…
Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks
Hao Zhang, Shizhen Xu, Graham Neubig +4
Recent deep learning (DL) models have moved beyond static network architectures to dynamic ones, handling data where the network structure changes every example, such as sequences…
Structured Generative Adversarial Networks
Zhijie Deng, Hao Zhang, Xiaodan Liang +4
We study the problem of conditional generative modeling based on designated semantics or structures. Existing models that build conditional generators either require massive labele…
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
Hao Zhang, Zeyu Zheng, Shizhen Xu +7
Deep learning models can take weeks to train on a single GPU-equipped machine, necessitating scaling out DL training to a GPU-cluster. However, current distributed DL implementatio…