604 citations · 2k across the 82 of their papers we have counts for
26 papers · 1 filter
Hessian-Aware Zeroth-Order Optimization for Black-Box Adversarial Attack
Haishan Ye, Zhichao Huang, Cong Fang +2
Zeroth-order optimization is an important research topic in machine learning. In recent years, it has become a key tool in black-box adversarial attack to neural network based imag…
Cross-database non-frontal facial expression recognition based on transductive deep transfer learning
Keyu Yan, Wenming Zheng, Tong Zhang +2
Cross-database non-frontal expression recognition is a very meaningful but rather difficult subject in the fields of computer vision and affect computing. In this paper, we propose…
Neural Machine Translation with Adequacy-Oriented Learning
Xiang Kong, Zhaopeng Tu, Shuming Shi +2
Although Neural Machine Translation (NMT) models have advanced state-of-the-art performance in machine translation, they face problems like the inadequate translation. We attribute…
Super-Identity Convolutional Neural Network for Face Hallucination
Kaipeng Zhang, Zhanpeng Zhang, Chia-Wen Cheng +4
Face hallucination is a generative task to super-resolve the facial image with low resolution while human perception of face heavily relies on identity information. However, previo…
Stochastic Primal-Dual Method for Empirical Risk Minimization with Per-Iteration Complexity
Conghui Tan, Tong Zhang, Shiqian Ma +1
Regularized empirical risk minimization problem with linear predictor appears frequently in machine learning. In this paper, we propose a new stochastic primal-dual method to solve…
Multi-Head Attention with Disagreement Regularization
Jian Li, Zhaopeng Tu, Baosong Yang +2
Multi-head attention is appealing for the ability to jointly attend to information from different representation subspaces at different positions. In this work, we introduce a disa…
Modeling Localness for Self-Attention Networks
Baosong Yang, Zhaopeng Tu, Derek F. Wong +3
Self-attention networks have proven to be of profound value for its strength of capturing global dependencies. In this work, we propose to model localness for self-attention networ…
Exploiting Deep Representations for Neural Machine Translation
Zi-Yi Dou, Zhaopeng Tu, Xing Wang +2
Advanced neural machine translation (NMT) models generally implement encoder and decoder as multiple layers, which allows systems to model complex functions and capture complicated…
Orthogonal Deep Features Decomposition for Age-Invariant Face Recognition
Yitong Wang, Dihong Gong, Zheng Zhou +5
As facial appearance is subject to significant intra-class variations caused by the aging process over time, age-invariant face recognition (AIFR) remains a major challenge in face…
Modeling Varying Camera-IMU Time Offset in Optimization-Based Visual-Inertial Odometry
Yonggen Ling, Linchao Bao, Zequn Jie +6
Combining cameras and inertial measurement units (IMUs) has been proven effective in motion tracking, as these two sensing modalities offer complementary characteristics that are s…
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space
Jiechao Xiong, Qing Wang, Zhuoran Yang +7
Most existing deep reinforcement learning (DRL) frameworks consider either discrete action space or continuous action space solely. Motivated by applications in computer games, we…
Fully Implicit Online Learning
Chaobing Song, Ji Liu, Han Liu +2
Regularized online learning is widely used in machine learning applications. In online learning, performing exact minimization ( implicit update) is known to be beneficial t…
TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game
Peng Sun, Xinghai Sun, Lei Han +8
Starcraft II (SC2) is widely considered as the most challenging Real Time Strategy (RTS) game. The underlying challenges include a large observation space, a huge (continuous and i…
Video Re-localization
Yang Feng, Lin Ma, Wei Liu +2
Many methods have been developed to help people find the video contents they want efficiently. However, there are still some unsolved problems in this area. For example, given a qu…
End-to-end Active Object Tracking and Its Real-world Deployment via Reinforcement Learning
Wenhan Luo, Peng Sun, Fangwei Zhong +3
We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) as input and produces the corresponding camera control signals as output (e.g., m…
Recurrent Fusion Network for Image Captioning
Wenhao Jiang, Lin Ma, Yu-Gang Jiang +2
Recently, much advance has been made in image captioning, and an encoder-decoder framework has been adopted by all the state-of-the-art models. Under this framework, an input image…
Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks
Minjun Li, Haozhi Huang, Lin Ma +3
Recent studies on unsupervised image-to-image translation have made a remarkable progress by training a pair of generative adversarial networks with a cycle-consistent loss. Howeve…
When Work Matters: Transforming Classical Network Structures to Graph CNN
Wenting Zhao, Chunyan Xu, Zhen Cui +4
Numerous pattern recognition applications can be formed as learning from graph-structured data, including social network, protein-interaction network, the world wide web data, know…
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator
Cong Fang, Chris Junchi Li, Zhouchen Lin +1
In this paper, we propose a new technique named \textit{Stochastic Path-Integrated Differential EstimatoR} (SPIDER), which can be used to track many deterministic quantities of int…
An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method
Li Shen, Peng Sun, Yitong Wang +2
We propose a novel algorithmic framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-gradient (VMOR-HPE) method with a global convergence guarantee for the maximal monoto…
Safe Element Screening for Submodular Function Minimization
Weizhong Zhang, Bin Hong, Lin Ma +2
Submodular functions are discrete analogs of convex functions, which have applications in various fields, including machine learning and computer vision. However, in large-scale ap…
Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset
Xinpeng Chen, Jingyuan Chen, Lin Ma +4
Nowadays, billions of videos are online ready to be viewed and shared. Among an enormous volume of videos, some popular ones are widely viewed by online users while the majority at…
QuaSE: Accurate Text Style Transfer under Quantifiable Guidance
Yi Liao, Lidong Bing, Piji Li +3
We propose the task of Quantifiable Sequence Editing (QuaSE): editing an input sequence to generate an output sequence that satisfies a given numerical outcome value measuring a ce…
Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective
Jing Zhang, Tong Zhang, Yuchao Dai +2
The success of current deep saliency detection methods heavily depends on the availability of large-scale supervision in the form of per-pixel labeling. Such supervision, while lab…