no code implementations • COLING 2022 • Xu Zhang, Zejie Liu, Yanzheng Xiang, Deyu Zhou
However such way might not fully explore the knowledge in PTMs as it is constrained by the difficulty of the task.
no code implementations • 8 Mar 2023 • Xu Zhang, Wenpeng Li, Yunfeng Shao, Yinchuan Li
data, we propose a clustered Bayesian FL model named cFedbayes by learning different prior distributions for different clients.
1 code implementation • 28 Feb 2023 • Xu Zhang, Marcos M. Vasconcelos
We consider the following scenario: multiple pairs of agents communicating strategically over shared communication networks in the presence of a jammer who may launch a denial-of-service.
no code implementations • 5 Jan 2023 • Haowen Zhao, Xu Zhang, Maoqi Chen, Ping Zhou
For decomposing experimental SEMG data, the proposed online method was able to extract an average of 12. 00 +- 3. 46 MUs per trial, with a matching rate of 90. 38% compared with results from the expert-guided offline decomposition.
no code implementations • 3 Jan 2023 • Hao Fang, Ajian Liu, Jun Wan, Sergio Escalera, Chenxu Zhao, Xu Zhang, Stan Z. Li, Zhen Lei
In order to promote relevant research and fill this gap in the community, we collect a large-scale Surveillance High-Fidelity Mask (SuHiFiMask) dataset captured under 40 surveillance scenes, which has 101 subjects from different age groups with 232 3D attacks (high-fidelity masks), 200 2D attacks (posters, portraits, and screens), and 2 adversarial attacks.
1 code implementation • 15 Dec 2022 • Zhihao LI, Ming Lu, Xu Zhang, Xin Feng, M. Salman Asif, Zhan Ma
Conventional cameras capture image irradiance on a sensor and convert it to RGB images using an image signal processor (ISP).
1 code implementation • 2 Dec 2022 • Sheng Liu, Xu Zhang, Nitesh Sekhar, Yue Wu, Prateek Singhal, Carlos Fernandez-Granda
Empirical studies suggest that machine learning models trained with empirical risk minimization (ERM) often rely on attributes that may be spuriously correlated with the class labels.
no code implementations • 16 Sep 2022 • Xu Zhang, Xiaojun Wan
In view of the importance of data augmentation in APE, we separately study the impact of the construction method of artificial corpora and artificial data domain on the performance of APE models.
no code implementations • 23 Jun 2022 • Xu Zhang, Wen Wang, Zhe Chen, Yufei Xu, Jing Zhang, DaCheng Tao
Motivated by the progress of visual-language research, we propose that pre-trained language models (e. g., CLIP) can facilitate animal pose estimation by providing rich prior knowledge for describing animal keypoints in text.
no code implementations • 16 Jun 2022 • Xu Zhang, Yinchuan Li, Wenpeng Li, Kaiyang Guo, Yunfeng Shao
Federated learning faces huge challenges from model overfitting due to the lack of data and statistical diversity among clients.
no code implementations • 19 May 2022 • Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, Qing He
Specifically, we build the personalized soft prefix prompt via a prompt generator based on user profiles and enable a sufficient training of prompts via a prompt-oriented contrastive learning with both prompt- and behavior-based augmentations.
1 code implementation • 10 May 2022 • Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xiang Ao, Xu Zhang, Leyu Lin, Qing He
In this work, we define the selective fairness task, where users can flexibly choose which sensitive attributes should the recommendation model be bias-free.
no code implementations • 4 Apr 2022 • Wenhui Ren, Weikang Li, Shibo Xu, Ke Wang, Wenjie Jiang, Feitong Jin, Xuhao Zhu, Jiachen Chen, Zixuan Song, Pengfei Zhang, Hang Dong, Xu Zhang, Jinfeng Deng, Yu Gao, Chuanyu Zhang, Yaozu Wu, Bing Zhang, Qiujiang Guo, Hekang Li, Zhen Wang, Jacob Biamonte, Chao Song, Dong-Ling Deng, H. Wang
Our results reveal experimentally a crucial vulnerability aspect of quantum learning systems under adversarial scenarios and demonstrate an effective defense strategy against adversarial attacks, which provide a valuable guide for quantum artificial intelligence applications with both near-term and future quantum devices.
1 code implementation • 1 Apr 2022 • Xu Zhang, Marcos M. Vasconcelos
We consider a sensor-receiver pair communicating over a wireless channel in the presence of a jammer who may launch a denial-of-service attack.
1 code implementation • 20 Mar 2022 • Yiqing Wu, Ruobing Xie, Yongchun Zhu, Xiang Ao, Xin Chen, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Qing He
We argue that MBR models should: (1) model the coarse-grained commonalities between different behaviors of a user, (2) consider both individual sequence view and global graph view in multi-behavior modeling, and (3) capture the fine-grained differences between multiple behaviors of a user.
no code implementations • 26 Jan 2022 • Xu Zhang, LianWu Chen, Xiguang Zheng, Xinlei Ren, Chen Zhang, Liang Guo, Bing Yu
Speech enhancement methods based on deep learning have surpassed traditional methods.
no code implementations • 5 Jan 2022 • Xu Zhang, Jian Yang, Haoyang Huang, Shuming Ma, Dongdong Zhang, Jinlong Li, Furu Wei
Existing document-level neural machine translation (NMT) models have sufficiently explored different context settings to provide guidance for target generation.
1 code implementation • CVPR 2022 • Jiaxu Miao, Xiaohan Wang, Yu Wu, Wei Li, Xu Zhang, Yunchao Wei, Yi Yang
In contrast, our large-scale VIdeo Panoptic Segmentation in the Wild (VIPSeg) dataset provides 3, 536 videos and 84, 750 frames with pixel-level panoptic annotations, covering a wide range of real-world scenarios and categories.
no code implementations • 17 Nov 2021 • Xinxing Wu, Tao Wang, Qian Liu, Peide Liu, Guanrong Chen, Xu Zhang
By introducing a new operator for IFVs via the linear order based on a score function and an accuracy function, we show that such an operator is a strong negation on IFVs.
no code implementations • 28 Oct 2021 • Tianyue Zheng, Zhe Chen, Chao Cai, Jun Luo, Xu Zhang
Given the significant amount of time people spend in vehicles, health issues under driving condition have become a major concern.
1 code implementation • 21 Oct 2021 • Yongchun Zhu, Zhenwei Tang, Yudan Liu, Fuzhen Zhuang, Ruobing Xie, Xu Zhang, Leyu Lin, Qing He
Specifically, a meta network fed with users' characteristic embeddings is learned to generate personalized bridge functions to achieve personalized transfer of preferences for each user.
1 code implementation • INTERSPEECH 2021 2021 • Xinlei Ren, Xu Zhang, LianWu Chen, Xiguang Zheng, Chen Zhang, Liang Guo, Bing Yu
In this work, a new causal U-net based multiple-in-multiple-out structure is proposed for real-time multi-channel speech enhancement.
no code implementations • 12 Jul 2021 • Xiaofeng Liu, Yinchuan Li, Qing Wang, Xu Zhang, Yunfeng Shao, Yanhui Geng
By incorporating an approximated L1-norm and the correlation between client models and global model into standard FL loss function, the performance on statistical diversity data is improved and the communicational and computational loads required in the network are reduced compared with non-sparse FL.
3 code implementations • 31 May 2021 • Yongchun Zhu, Yudan Liu, Ruobing Xie, Fuzhen Zhuang, Xiaobo Hao, Kaikai Ge, Xu Zhang, Leyu Lin, Juan Cao
Besides, MetaHeac has been successfully deployed in WeChat for the promotion of both contents and advertisements, leading to great improvement in the quality of marketing.
no code implementations • 11 May 2021 • Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang, Ruobing Xie, Dongbo Xi, Xu Zhang, Leyu Lin, Qing He
With the advantage of meta learning which has good generalization ability to novel tasks, we propose a transfer-meta framework for CDR (TMCDR) which has a transfer stage and a meta stage.
no code implementations • 11 May 2021 • Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin, Juan Cao
The cold item ID embedding has two main problems: (1) A gap is existing between the cold ID embedding and the deep model.
no code implementations • 22 Mar 2021 • Yanzhao Li, Ju'e Guo, Yongwu Li, Xu Zhang
Based on venture capitalists' understanding of future preferences, we consider four types of venture capitalists, namely time-consistent venture capitalists, venture capitalists who only realize critical time point inconsistency, naive venture capitalists and sophisticated venture capitalists, of which the latter three are time-inconsistent.
no code implementations • 11 Mar 2021 • Xingyu Jiang, Mingyang Qin, Xinjian Wei, Zhongpei Feng, Jiezun Ke, Haipeng Zhu, Fucong Chen, Liping Zhang, Li Xu, Xu Zhang, Ruozhou Zhang, Zhongxu Wei, Peiyu Xiong, Qimei Liang, Chuanying Xi, Zhaosheng Wang, Jie Yuan, Beiyi Zhu, Kun Jiang, Ming Yang, Junfeng Wang, Jiangping Hu, Tao Xiang, Brigitte Leridon, Rong Yu, Qihong Chen, Kui Jin, Zhongxian Zhao
Iron selenide (FeSe) - the structurally simplest iron-based superconductor, has attracted tremendous interest in the past years.
Superconductivity
1 code implementation • 4 Mar 2021 • Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, Philip S. Yu
"Top Stories" is a novel friend-enhanced recommendation engine in WeChat, in which users can read articles based on preferences of both their own and their friends.
Graph Representation Learning
Social and Information Networks
no code implementations • 22 Feb 2021 • Chaojun Xiao, Ruobing Xie, Yuan YAO, Zhiyuan Liu, Maosong Sun, Xu Zhang, Leyu Lin
Existing sequential recommendation methods rely on large amounts of training data and usually suffer from the data sparsity problem.
1 code implementation • LREC 2022 • Wenhao Zhu, ShuJian Huang, Tong Pu, Pingxuan Huang, Xu Zhang, Jian Yu, Wei Chen, Yanfeng Wang, Jiajun Chen
Previous research for adapting a general neural machine translation (NMT) model into a specific domain usually neglects the diversity in translation within the same domain, which is a core problem for domain adaptation in real-world scenarios.
no code implementations • 22 Dec 2020 • Yao Zhang, Xu Zhang, Jun Wang, Hongru Liang, Wenqiang Lei, Zhe Sun, Adam Jatowt, Zhenglu Yang
The current methods for the link prediction taskhavetwonaturalproblems:1)the relation distributions in KGs are usually unbalanced, and 2) there are many unseen relations that occur in practical situations.
1 code implementation • COLING 2020 • Xu Zhang, Yifeng Li, Wenpeng Lu, Ping Jian, Guoqiang Zhang
Sentence intention matching is vital for natural language understanding.
1 code implementation • ACM International Conference on Information and Knowledge Management 2020 • Su Yan, Xin Chen, Ran Huo, Xu Zhang, Leyu Lin
User profiling is one of the most important components in recommendation systems, where a user is profiled using demographic (e. g. gender, age, and location) and user behavior information (e. g. browsing and search history).
no code implementations • 17 Aug 2020 • Jing Zhang, Deng Liang, Aiping Liu, Min Gao, Xiang Chen, Xu Zhang, Xun Chen
MLBF-Net is composed of three components: 1) multiple lead-specific branches for learning the diversity of multi-lead ECG; 2) cross-lead features fusion by concatenating the output feature maps of all branches for learning the integrity of multi-lead ECG; 3) multi-loss co-optimization for all the individual branches and the concatenated network.
no code implementations • 19 May 2020 • Bo Xu, Xu Zhang, Zhixin Li, Matt Leotta, Shih-Fu Chang, Jie Shan
For points that belong to the same roof shape, a multi-cue, hierarchical RANSAC approach is proposed for efficient and reliable segmenting and reconstructing the building point cloud.
no code implementations • 30 Mar 2020 • Pei Zhang, Xu Zhang, Wei Chen, Jian Yu, Yan-Feng Wang, Deyi Xiong
In this paper, we propose a new framework to model cross-sentence dependencies by training neural machine translation (NMT) to predict both the target translation and surrounding sentences of a source sentence.
no code implementations • 8 Mar 2020 • Yang Feng, Futang Peng, Xu Zhang, Wei Zhu, Shanfeng Zhang, Howard Zhou, Zhen Li, Tom Duerig, Shih-Fu Chang, Jiebo Luo
Therefore, we propose to distill the knowledge in multiple specialists into a universal embedding to solve this problem.
1 code implementation • 15 Jul 2019 • Xu Zhang, Svebor Karaman, Shih-Fu Chang
By using the simulated images to train a spectrum based classifier, even without seeing the fake images produced by the targeted GAN model during training, our approach achieves state-of-the-art performances on detecting fake images generated by popular GAN models such as CycleGAN.
1 code implementation • 12 Jun 2019 • Yudan Liu, Kaikai Ge, Xu Zhang, Leyu Lin
Recently, deep learning models play more and more important roles in contents recommender systems.
1 code implementation • 29 May 2019 • Yang Yao, Xu Zhang, Baile Xu, Furao Shen, Jian Zhao
Recent studies have demonstrated that the convolutional networks heavily rely on the quality and quantity of generated features.
no code implementations • 20 May 2019 • Xu Zhang, Yang Yao, Baile Xu, Lekun Mao, Furao Shen, Jian Zhao, QIngwei Lin
In this paper, it is the first time to discuss the difficulty without support of old classes in class incremental learning, which is called as softmax suppression problem.
1 code implementation • CVPR 2019 • Mang Ye, Xu Zhang, Pong C. Yuen, Shih-Fu Chang
This paper studies the unsupervised embedding learning problem, which requires an effective similarity measurement between samples in low-dimensional embedding space.
1 code implementation • 18 Jan 2019 • Qi Lü, Xu Zhang
By means of a new global Carleman estimate, we establish the exact controllability of our stochastic wave equation with three controls.
Optimization and Control 93B05, 60H15, 93B07, 35B45
1 code implementation • 17 Jan 2019 • Weilian Song, Scott Workman, Armin Hadzic, Xu Zhang, Eric Green, Mei Chen, Reginald Souleyrette, Nathan Jacobs
An emerging approach for conducting such assessments in the United States is through the US Road Assessment Program (usRAP), which rates roads from highest risk (1 star) to lowest (5 stars).
no code implementations • 14 Jan 2019 • Yi Zhen, Hang Chen, Xu Zhang, Meng Liu, Xin Meng, Jian Zhang, Jiantao Pu
To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.
1 code implementation • 4 Jan 2019 • Qi Lu, Xu Zhang
It is a longstanding unsolved problem to characterize the optimal feedbacks for general SLQs (i. e., stochastic linear quadratic control problems) with random coefficients in infinite dimensions; while the same problem but in finite dimensions was just addressed in a recent work [36].
Optimization and Control Probability 60H15, 93E20, 60H25, 49J30
1 code implementation • 18 Nov 2018 • Qi Lu, Haisen Zhang, Xu Zhang
In this paper, we establish some second order necessary/sufficient optimality conditions for optimal control problems of stochastic evolution equations in infinite dimensions.
Optimization and Control Primary 93E20, Secondary, 60H07, 60H15
no code implementations • 12 Oct 2018 • Linglin Kong, Li Ling, Xu Zhang
This problem is NP-hard, so we propose a heuristic algorithm based on semi-definite relaxation (SDR) programming to solve it.
Signal Processing
1 code implementation • ICLR 2019 • Xu Zhang, Felix Xinnan Yu, Svebor Karaman, Wei zhang, Shih-Fu Chang
Metric learning aims at learning a distance which is consistent with the semantic meaning of the samples.
1 code implementation • 7 Oct 2017 • Ruriko Yoshida, Leon Zhang, Xu Zhang
Principal component analysis is a widely-used method for the dimensionality reduction of a given data set in a high-dimensional Euclidean space.
Combinatorics Populations and Evolution
2 code implementations • ICCV 2017 • Xu Zhang, Felix X. Yu, Sanjiv Kumar, Shih-Fu Chang
We propose a simple, yet powerful regularization technique that can be used to significantly improve both the pairwise and triplet losses in learning local feature descriptors.
1 code implementation • CVPR 2017 • Xu Zhang, Felix X. Yu, Svebor Karaman, Shih-Fu Chang
Specifically, we extend the covariant constraint proposed by Lenc and Vedaldi by defining the concepts of "standard patch" and "canonical feature" and leverage these to train a novel robust covariant detector.
1 code implementation • Computer Vision and Pattern Recognition 2017 • Xu Zhang, Felix X. Yu, Svebor Karaman, Shih-Fu Chang
Specifically, we extend the covariant constraint proposed by Lenc and Vedaldi [8] by defining the concepts of “standard patch” and “canonical feature” and leverage these to train a novel robust covariant detector.
no code implementations • 27 Aug 2016 • Jianhong Wang, Tian Lan, Xu Zhang, Limin Luo
This paper presents a novel mid-level representation for action recognition, named spatio-temporal aware non-negative component representation (STANNCR).
no code implementations • ICCV 2015 • Xu Zhang, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar, Shengjin Wang, Shi-Fu Chang
We propose a family of structured matrices to speed up orthogonal projections for high-dimensional data commonly seen in computer vision applications.
no code implementations • 2 Mar 2015 • Xu Zhang, Felix Xinnan Yu, Shih-Fu Chang, Shengjin Wang
In this paper, we propose a new domain adaptation framework named Deep Transfer Network (DTN), where the highly flexible deep neural networks are used to implement such a distribution matching process.
no code implementations • 14 May 2014 • Tieming Chen, Xu Zhang, Shichao Jin, Okhee Kim
In order to achieve high efficiency of classification in intrusion detection, a compressed model is proposed in this paper which combines horizontal compression with vertical compression.