55 citations · 147 across the 11 of their papers we have counts for
11 papers
Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness
Zhanhao Hu, Jun Zhu, Bo Zhang +1
Recent works found that deep neural networks (DNNs) can be fooled by adversarial examples, which are crafted by adding adversarial noise on clean inputs. The accuracy of DNNs on ad…
Understanding Adversarial Attacks on Observations in Deep Reinforcement Learning
You Qiaoben, Chengyang Ying, Xinning Zhou +3
Deep reinforcement learning models are vulnerable to adversarial attacks that can decrease a victim's cumulative expected reward by manipulating the victim's observations. Despite…
Joint Cluster Unary Loss for Efficient Cross-Modal Hashing
Shifeng Zhang, Jianmin Li, Bo Zhang
With the rapid growth of various types of multimodal data, cross-modal deep hashing has received broad attention for solving cross-modal retrieval problems efficiently. Most cross-…
Pairwise Teacher-Student Network for Semi-Supervised Hashing
Shifeng Zhang, Jianmin Li, Bo Zhang
Hashing method maps similar high-dimensional data to binary hashcodes with smaller hamming distance, and it has received broad attention due to its low storage cost and fast retrie…
Function Space Particle Optimization for Bayesian Neural Networks
Ziyu Wang, Tongzheng Ren, Jun Zhu +1
While Bayesian neural networks (BNNs) have drawn increasing attention, their posterior inference remains challenging, due to the high-dimensional and over-parameterized nature. To…
Semi-crowdsourced Clustering with Deep Generative Models
Yucen Luo, Tian Tian, Jiaxin Shi +2
We consider the semi-supervised clustering problem where crowdsourcing provides noisy information about the pairwise comparisons on a small subset of data, i.e., whether a sample p…
Interlinked Convolutional Neural Networks for Face Parsing
Yisu Zhou, Xiaolin Hu, Bo Zhang
Face parsing is a basic task in face image analysis. It amounts to labeling each pixel with appropriate facial parts such as eyes and nose. In the paper, we present a interlinked c…
Message Passing Stein Variational Gradient Descent
Jingwei Zhuo, Chang Liu, Jiaxin Shi +3
Stein variational gradient descent (SVGD) is a recently proposed particle-based Bayesian inference method, which has attracted a lot of interest due to its remarkable approximation…
Scalable Discrete Supervised Hash Learning with Asymmetric Matrix Factorization
Shifeng Zhang, Jianmin Li, Jinma Guo +1
Hashing method maps similar data to binary hashcodes with smaller hamming distance, and it has received a broad attention due to its low storage cost and fast retrieval speed. Howe…
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation
Bei Chen, Ning Chen, Jun Zhu +2
We present a discriminative nonparametric latent feature relational model (LFRM) for link prediction to automatically infer the dimensionality of latent features. Under the generic…
Improved Bayesian Logistic Supervised Topic Models with Data Augmentation
Jun Zhu, Xun Zheng, Bo Zhang
Supervised topic models with a logistic likelihood have two issues that potentially limit their practical use: 1) response variables are usually over-weighted by document word coun…