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2020 – today
- 2021
[j57]Bin Chen
, Weijun Fang, Shu-Tao Xia, Jie Hao, Fang-Wei Fu:
Improved Bounds and Singleton-Optimal Constructions of Locally Repairable Codes With Minimum Distance 5 and 6. IEEE Trans. Inf. Theory 67(1): 217-231 (2021)- [i60]Jiawang Bai, Baoyuan Wu, Yong Zhang, Yiming Li, Zhifeng Li, Shu-Tao Xia:
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits. CoRR abs/2102.10496 (2021) - [i59]Yiming Li, Yanjie Li, Yalei Lv, Yong Jiang, Shu-Tao Xia:
Hidden Backdoor Attack against Semantic Segmentation Models. CoRR abs/2103.04038 (2021) - [i58]Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang:
Improving Adversarial Robustness via Channel-wise Activation Suppressing. CoRR abs/2103.08307 (2021) - [i57]Yiming Li, Tongqing Zhai, Yong Jiang, Zhifeng Li, Shu-Tao Xia:
Backdoor Attack in the Physical World. CoRR abs/2104.02361 (2021) - [i56]Yanjie Li, Shoukui Zhang, Zhicheng Wang, Sen Yang, Wankou Yang, Shu-Tao Xia, Erjin Zhou:
TokenPose: Learning Keypoint Tokens for Human Pose Estimation. CoRR abs/2104.03516 (2021) - 2020
- [j56]Jie Hao, Kenneth W. Shum, Shu-Tao Xia, Deyin Li:
Optimal Locally Repairable Codes for Parallel Reading. IEEE Access 8: 80447-80453 (2020) - [j55]Xiyu Yan, Huihui Gong, Yong Jiang, Shu-Tao Xia, Feng Zheng, Xinge You, Ling Shao:
Video scene parsing: An overview of deep learning methods and datasets. Comput. Vis. Image Underst. 201: 103077 (2020) - [j54]Jiawei Li, Yiming Li, Xingchun Xiang, Shu-Tao Xia, Siyi Dong, Yun Cai:
TNT: An Interpretable Tree-Network-Tree Learning Framework using Knowledge Distillation. Entropy 22(11): 1203 (2020) - [j53]Jiacheng Yang, Bin Chen, Shu-Tao Xia:
Mean-removed product quantization for large-scale image retrieval. Neurocomputing 406: 77-88 (2020) - [j52]Zhendong Peng, Xi Xiao, Guangwu Hu, Arun Kumar Sangaiah, Mohammed Atiquzzaman, Shutao Xia:
ABFL: An autoencoder based practical approach for software fault localization. Inf. Sci. 510: 108-121 (2020) - [j51]Xi Xiao, Dianyan Zhang, Guangwu Hu, Yong Jiang, Shutao Xia:
CNN-MHSA: A Convolutional Neural Network and multi-head self-attention combined approach for detecting phishing websites. Neural Networks 125: 303-312 (2020) - [j50]Jie Hao, Shu-Tao Xia, Kenneth W. Shum, Bin Chen, Fang-Wei Fu, Yixian Yang:
Bounds and Constructions of Locally Repairable Codes: Parity-Check Matrix Approach. IEEE Trans. Inf. Theory 66(12): 7465-7474 (2020) - [j49]Songtao Wang, Dan Li, Yang Cheng, Jinkun Geng, Yanshu Wang, Shuai Wang, Shutao Xia, Jianping Wu:
A Scalable, High-Performance, and Fault-Tolerant Network Architecture for Distributed Machine Learning. IEEE/ACM Trans. Netw. 28(4): 1752-1764 (2020) - [c126]Yan Feng, Bin Chen, Tao Dai, Shu-Tao Xia:
Adversarial Attack on Deep Product Quantization Network for Image Retrieval. AAAI 2020: 10786-10793 - [c125]Xuesong Chen, Xiyu Yan, Feng Zheng, Yong Jiang, Shu-Tao Xia, Yong Zhao, Rongrong Ji:
One-Shot Adversarial Attacks on Visual Tracking With Dual Attention. CVPR 2020: 10173-10182 - [c124]Bowen Zhao, Xi Xiao, Guojun Gan, Bin Zhang, Shu-Tao Xia:
Maintaining Discrimination and Fairness in Class Incremental Learning. CVPR 2020: 13205-13214 - [c123]Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo:
Improving Query Efficiency of Black-Box Adversarial Attack. ECCV (25) 2020: 101-116 - [c122]Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-Hui Yang:
Targeted Attack for Deep Hashing Based Retrieval. ECCV (1) 2020: 618-634 - [c121]Haoyu Liang, Zhihao Ouyang, Yuyuan Zeng, Hang Su, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang:
Training Interpretable Convolutional Neural Networks by Differentiating Class-Specific Filters. ECCV (2) 2020: 622-638 - [c120]Haoxiang Zhong, Xiyu Yan, Yong Jiang, Shu-Tao Xia:
Improved Real-Time Visual Tracking via Adversarial Learning. ICASSP 2020: 1853-1857 - [c119]Peidong Liu, Xiyu Yan, Yong Jiang, Shu-Tao Xia:
Deep Flow Collaborative Network for Online Visual Tracking. ICASSP 2020: 2598-2602 - [c118]Xiyu Yan, Xuesong Chen, Yong Jiang, Shu-Tao Xia, Yong Zhao, Feng Zheng:
Hijacking Tracker: A Powerful Adversarial Attack on Visual Tracking. ICASSP 2020: 2897-2901 - [c117]Bowen Zhao, Xi Xiao, Wanpeng Zhang, Bin Zhang, Guojun Gan, Shutao Xia:
Self-Paced Probabilistic Principal Component Analysis For Data With Outliers. ICASSP 2020: 3737-3741 - [c116]Yuyuan Zeng, Tao Dai, Shu-Tao Xia:
Corrdrop: Correlation Based Dropout for Convolutional Neural Networks. ICASSP 2020: 3742-3746 - [c115]Xinyi Liu, Yang Bai, Shu-Tao Xia, Yong Jiang:
Self-Adaptive Feature Fool. ICASSP 2020: 4177-4181 - [c114]Zibin He, Tao Dai, Jian Lu, Yong Jiang, Shu-Tao Xia:
Fakd: Feature-Affinity Based Knowledge Distillation for Efficient Image Super-Resolution. ICIP 2020: 518-522 - [c113]Yuzhao Chen, Xi Xiao, Tao Dai, Shu-Tao Xia:
Hrnet: Hamiltonian Rescaling Network for Image Downscaling. ICIP 2020: 523-527 - [c112]Yuzhao Chen, Tao Dai, Xi Xiao, Jian Lu, Shu-Tao Xia:
Enhanced Image Restoration Via Supervised Target Feature Transfer. ICIP 2020: 1028-1032 - [c111]Jia Xu, Yiming Li, Yong Jiang, Shu-Tao Xia:
Adversarial Defense Via Local Flatness Regularization. ICIP 2020: 2196-2200 - [c110]Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma:
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. ICLR 2020 - [c109]Xianbin Lv, Dongxian Wu, Shu-Tao Xia:
Matrix Smoothing: A Regularization For Dnn With Transition Matrix Under Noisy Labels. ICME 2020: 1-6 - [c108]Qiang Li, Tao Dai, Shu-Tao Xia:
Progressive Splitting and Upscaling Structure for Super-Resolution. ICPR 2020: 8885-8891 - [c107]Shudeng Wu, Tao Dai, Guanghao Meng, Bin Chen, Jian Lu, Shu-Tao Xia:
Transferable Adversarial Attacks for Deep Scene Text Detection. ICPR 2020: 8945-8951 - [c106]Guanghao Meng, Tao Dai, Shudeng Wu, Bin Chen, Jian Lu, Yong Jiang, Shu-Tao Xia:
Sample-aware Data Augmentor for Scene Text Recognition. ICPR 2020: 9378-9385 - [c105]Yinghua Gao, Naiqi Li, Ning Ding, Yiming Li, Tao Dai, Shu-Tao Xia:
Generalized Local Aggregation for Large Scale Gaussian Process Regression. IJCNN 2020: 1-8 - [c104]Wenjie Li, Xue Yang, Xiaohu Tang, Shutao Xia:
SDCN: Sparsity and Diversity Driven Correlation Networks for Traffic Demand Forecasting. IJCNN 2020: 1-8 - [c103]Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shu-Tao Xia:
Temporal Calibrated Regularization for Robust Noisy Label Learning. IJCNN 2020: 1-8 - [c102]Weijun Fang, Bin Chen, Shu-Tao Xia, Fang-Wei Fu:
Complete Characterization of Optimal LRCs with Minimum Distance 6 and Locality 2: Improved Bounds and Constructions. ISIT 2020: 595-599 - [c101]Weijun Fang, Bin Chen, Shu-Tao Xia, Fang-Wei Fu:
Perfect LRCs and k-Optimal LRCs. ISIT 2020: 600-604 - [c100]Jie Hao, Jun Zhang, Shu-Tao Xia, Fang-Wei Fu, Yi-Xian Yang:
Weight Distributions of q-ary Optimal Locally Repairable Codes with Locality 2, Distance 5 and Even Dimension. ISIT 2020: 611-615 - [c99]Jiawei Li, Shu-Tao Xia, Qianggang Ding:
Multi-level Recognition on Falls from Activities of Daily Living. ICMR 2020: 464-471 - [c98]Tao Dai, Yan Feng, Dongxian Wu, Bin Chen, Jian Lu, Yong Jiang, Shu-Tao Xia:
DIPDefend: Deep Image Prior Driven Defense against Adversarial Examples. ACM Multimedia 2020: 1404-1412 - [c97]Naiqi Li, Wenjie Li, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia:
Stochastic Deep Gaussian Processes over Graphs. NeurIPS 2020 - [c96]Dongxian Wu, Shu-Tao Xia, Yisen Wang:
Adversarial Weight Perturbation Helps Robust Generalization. NeurIPS 2020 - [c95]Guorui Xie, Qing Li, Yong Jiang, Tao Dai, Gengbiao Shen, Rui Li, Richard O. Sinnott, Shutao Xia:
SAM: Self-Attention based Deep Learning Method for Online Traffic Classification. NetAI@SIGCOMM 2020: 14-20 - [i55]Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma:
Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets. CoRR abs/2002.05990 (2020) - [i54]Yan Feng, Xue Yang, Weijun Fang, Shu-Tao Xia, Xiaohu Tang:
Practical and Bilateral Privacy-preserving Federated Learning. CoRR abs/2002.09843 (2020) - [i53]Yan Feng, Bin Chen, Tao Dai, Shutao Xia:
Adversarial Attack on Deep Product Quantization Network for Image Retrieval. CoRR abs/2002.11374 (2020) - [i52]Yiming Li, Baoyuan Wu, Yan Feng, Yanbo Fan, Yong Jiang, Zhifeng Li, Shutao Xia:
Toward Adversarial Robustness via Semi-supervised Robust Training. CoRR abs/2003.06974 (2020) - [i51]Xianbin Lv, Dongxian Wu, Shu-Tao Xia:
Matrix Smoothing: A Regularization for DNN with Transition Matrix under Noisy Labels. CoRR abs/2003.11904 (2020) - [i50]Yiming Li, Tongqing Zhai, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shutao Xia:
Rethinking the Trigger of Backdoor Attack. CoRR abs/2004.04692 (2020) - [i49]Dongxian Wu, Yisen Wang, Shutao Xia:
Revisiting Loss Landscape for Adversarial Robustness. CoRR abs/2004.05884 (2020) - [i48]Jiawang Bai, Bin Chen, Yiming Li, Dongxian Wu, Weiwei Guo, Shu-Tao Xia, En-Hui Yang:
Targeted Attack for Deep Hashing based Retrieval. CoRR abs/2004.07955 (2020) - [i47]Weijun Fang, Jun Zhang, Shu-Tao Xia, Fang-Wei Fu:
A Note on Self-Dual Generalized Reed-Solomon Codes. CoRR abs/2005.11732 (2020) - [i46]Weijun Fang, Shu-Tao Xia, Fang-Wei Fu:
Construction of MDS Euclidean Self-Dual Codes via Two Subsets. CoRR abs/2006.00457 (2020) - [i45]Yan Feng, Baoyuan Wu, Yanbo Fan, Zhifeng Li, Shutao Xia:
Efficient Black-Box Adversarial Attack Guided by the Distribution of Adversarial Perturbations. CoRR abs/2006.08538 (2020) - [i44]Dongxian Wu, Yisen Wang, Zhuobin Zheng, Shutao Xia:
Temporal Calibrated Regularization for Robust Noisy Label Learning. CoRR abs/2007.00240 (2020) - [i43]Haoyu Liang, Zhihao Ouyang, Yuyuan Zeng, Hang Su, Zihao He, Shu-Tao Xia, Jun Zhu, Bo Zhang:
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters. CoRR abs/2007.08194 (2020) - [i42]Yiming Li, Baoyuan Wu, Yong Jiang, Zhifeng Li, Shu-Tao Xia:
Backdoor Learning: A Survey. CoRR abs/2007.08745 (2020) - [i41]Jie Fang, Jianwu Lin, Shutao Xia, Yong Jiang, Zhikang Xia, Xiang Liu:
Neural Network-based Automatic Factor Construction. CoRR abs/2008.06225 (2020) - [i40]Yiming Li, Jiawang Bai, Jiawei Li, Xue Yang, Yong Jiang, Shu-Tao Xia:
Rectified Decision Trees: Exploring the Landscape of Interpretable and Effective Machine Learning. CoRR abs/2008.09413 (2020) - [i39]Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo:
Improving Query Efficiency of Black-box Adversarial Attack. CoRR abs/2009.11508 (2020) - [i38]Yiming Li, Ziqi Zhang, Jiawang Bai, Baoyuan Wu, Yong Jiang, Shu-Tao Xia:
Open-sourced Dataset Protection via Backdoor Watermarking. CoRR abs/2010.05821 (2020) - [i37]Xingchun Xiang, Qingtao Tang, Huaixuan Zhang, Tao Dai, Jiawei Li, Shu-Tao Xia:
JSRT: James-Stein Regression Tree. CoRR abs/2010.09022 (2020) - [i36]Tongqing Zhai, Yiming Li, Ziqi Zhang, Baoyuan Wu, Yong Jiang, Shu-Tao Xia:
Backdoor Attack against Speaker Verification. CoRR abs/2010.11607 (2020) - [i35]Shudeng Wu, Tao Dai, Shu-Tao Xia:
DPAttack: Diffused Patch Attacks against Universal Object Detection. CoRR abs/2010.11679 (2020) - [i34]Bowen Zhao, Chen Chen, Wanpeng Xiao, Xi Xiao, Qi Ju, Shutao Xia:
Towards A Category-extended Object Detector without Relabeling or Conflicts. CoRR abs/2012.14115 (2020)
2010 – 2019
- 2019
- [j48]Haoxi Cong, Minhao Zhang, Shu-Tao Xia, Qingmin Li:
Protective Performance of Different Passivators on Oil-Paper Insulation Containing Multiple Corrosive Sulphides. IEEE Access 7: 4083-4090 (2019) - [j47]Jiawei Li, Yiming Li, Jiacheng Yang, Taian Guo, Shu-Tao Xia:
UA-DRN: Unbiased Aggregation of Deep Neural Networks for Regression Ensemble. Aust. J. Intell. Inf. Process. Syst. 15(2): 86-93 (2019) - [j46]Xi Xiao, Rui Li, Haitao Zheng, Runguo Ye, Arun Kumar Sangaiah, Shutao Xia:
Novel dynamic multiple classification system for network traffic. Inf. Sci. 479: 526-541 (2019) - [j45]Jin-Yuan Chen, Hai-Tao Zheng, Yong Jiang, Shu-Tao Xia, Cong-Zhi Zhao:
A probabilistic model for semantic advertising. Knowl. Inf. Syst. 59(2): 387-412 (2019) - [j44]Bin Chen, Weijun Fang, Shu-Tao Xia, Fang-Wei Fu:
Constructions of Optimal $(r, \delta)$ Locally Repairable Codes via Constacyclic Codes. IEEE Trans. Commun. 67(8): 5253-5263 (2019) - [j43]Weizhi Lu, Weiyu Li, Wei Zhang, Shu-Tao Xia:
Expander Recovery Performance of Bipartite Graphs With Girth Greater Than 4. IEEE Trans. Signal Inf. Process. over Networks 5(3): 418-427 (2019) - [c94]Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang:
Second-Order Attention Network for Single Image Super-Resolution. CVPR 2019: 11065-11074 - [c93]Zhixiang Wang, Xi Xiao, Guangwu Hu, Yao Yao, Dianyan Zhang, Zhendong Peng, Qing Li, Shutao Xia:
Non-local Self-attention Structure for Function Approximation in Deep Reinforcement Learning. ICASSP 2019: 3042-3046 - [c92]Yang Bai, Yan Feng, Yisen Wang, Tao Dai, Shutao Xia, Yong Jiang:
Hilbert-Based Generative Defense for Adversarial Examples. ICCV 2019: 4783-4792 - [c91]Dario Fuoli, Xiaoyong Shen, Shutao Xia, Yurong Dai, Jiaya Jia, Peng Yi, Zhongyuan Wang, Kui Jiang, Junjun Jiang, Jiayi Ma, Zhiwei Zhong, Shuhang Gu, Chenyang Wang, Junjun Jiang, Xianming Liu, Radu Timofte, Xin Tao, Wenbo Li, Taian Guo, Zijun Deng, Liying Lu, Tao Dai:
AIM 2019 Challenge on Video Extreme Super-Resolution: Methods and Results. ICCV Workshops 2019: 3467-3475 - [c90]Tao Dai, Hua Zha, Yong Jiang, Shu-Tao Xia:
Image Super-Resolution via Residual Block Attention Networks. ICCV Workshops 2019: 3879-3886 - [c89]Jiacheng Yang, Bin Chen, Shu-Tao Xia:
Mean-Removed Product Quantization for Approximate Nearest Neighbor Search. ICDM Workshops 2019: 711-718 - [c88]Qianggang Ding, Fan Yang, Jiawei Li, Sifan Wu, Bowen Zhao, Zhi Wang, Shu-Tao Xia:
RT-ADI: Fast Real-Time Video Representation for Multi-view Human Fall Detection. ICME Workshops 2019: 13-18 - [c87]Xiyu Yan, Yeli Xing, Zihao He, Tao Dai, Yong Jiang, Shu-Tao Xia:
Neural Style Transfer with Content Discrimination. ICME Workshops 2019: 78-83 - [c86]Huaixuan Zhang, Yuhai Lan, Tao Dai, Ruizhi Qiao, Ying Xu, Yao Yao, Shu-Tao Xia:
Residual Frame for Noisy Video Classification According to Perceptual Quality in Convolutional Neural Networks. ICME 2019: 242-247 - [c85]Zhihao Ouyang, Yan Feng, Zihao He, Tianbo Hao, Tao Dai, Shu-Tao Xia:
Attentiondrop for Convolutional Neural Networks. ICME 2019: 1342-1347 - [c84]Taian Guo, Tao Dai, Jiawei Li, Shu-Tao Xia:
Self-attentive Pyramid Network for Single Image De-raining. ICONIP (1) 2019: 390-401 - [c83]Xiyu Yan, Yong Jiang, Shuai Chen, Zihao He, Chunmei Li, Shu-Tao Xia, Tao Dai, Shuo Dong, Feng Zheng:
Automatic Grassland Degradation Estimation Using Deep Learning. IJCAI 2019: 6028-6034 - [c82]Bin Chen, Shu-Tao Xia, Jie Hao:
Improved bounds and Optimal Constructions of Locally Repairable Codes with distance 5 and 6. ISIT 2019: 2823-2827 - [c81]Jie Hao, Kenneth W. Shum, Shu-Tao Xia, Yi-Xian Yang:
Classification of Optimal Ternary (r, δ)-Locally Repairable Codes Attaining the Singleton-like Bound. ISIT 2019: 2828-2832 - [c80]Hongshan Li, Yu Guo, Zhi Wang, Shutao Xia, Wenwu Zhu:
AdaCompress: Adaptive Compression for Online Computer Vision Services. ACM Multimedia 2019: 2440-2448 - [c79]Xiaoteng Ma, Qing Li, Jimeng Chai, Xi Xiao, Shu-Tao Xia, Yong Jiang:
Steward: smart edge based joint QoE optimization for adaptive video streaming. NOSSDAV 2019: 31-36 - [c78]Jiawei Li, Xingchun Xiang, Tao Dai, Shu-Tao Xia:
Making Large Ensemble of Convolutional Neural Networks via Bootstrap Re-sampling. VCIP 2019: 1-4 - [i33]Yiming Li, Jiawang Bai, Qingtao Tang, Yong Jiang, Chun Li, Shutao Xia:
Multinomial Random Forests: Fill the Gap between Theoretical Consistency and Empirical Soundness. CoRR abs/1903.04003 (2019) - [i32]Jiawang Bai, Yiming Li, Jiawei Li, Yong Jiang, Shu-Tao Xia:
Rectified Decision Trees: Towards Interpretability, Compression and Empirical Soundness. CoRR abs/1903.05965 (2019) - [i31]Bowen Zhao, Xi Xiao, Wanpeng Zhang, Bin Zhang, Shutao Xia:
Self-Paced Probabilistic Principal Component Analysis for Data with Outliers. CoRR abs/1904.06546 (2019) - [i30]Yang Zhang, Qingtao Tang, Yiming Li, Weipeng Huang, Shutao Xia:
t-k-means: A k-means Variant with Robustness and Stability. CoRR abs/1907.07442 (2019) - [i29]Qianggang Ding, Sifan Wu, Hao Sun, Jiadong Guo, Shu-Tao Xia:
Adaptive Regularization of Labels. CoRR abs/1908.05474 (2019) - [i28]Hongshan Li, Yu Guo, Zhi Wang, Shutao Xia, Wenwu Zhu:
AdaCompress: Adaptive Compression for Online Computer Vision Services. CoRR abs/1909.08148 (2019) - [i27]Jia Xu, Yiming Li, Yang Bai, Yong Jiang, Shu-Tao Xia:
Adversarial Defense Via Local Flatness Regularization. CoRR abs/1910.12165 (2019) - [i26]Peidong Liu, Yiming Li, Yong Jiang, Shu-Tao Xia:
Visual Privacy Protection via Mapping Distortion. CoRR abs/1911.01769 (2019) - [i25]Peidong Liu, Xiyu Yan, Yong Jiang, Shu-Tao Xia:
Deep Flow Collaborative Network for Online Visual Tracking. CoRR abs/1911.01786 (2019) - [i24]Bowen Zhao, Xi Xiao, Guojun Gan, Bin Zhang, Shutao Xia:
Maintaining Discrimination and Fairness in Class Incremental Learning. CoRR abs/1911.07053 (2019) - [i23]Jie Fang, Jianwu Lin, Yong Jiang, Shutao Xia:
Prior Knowledge Neural Network for Automatic Feature Construction in Financial Time Series. CoRR abs/1912.06236 (2019) - [i22]Jie Fang, Zhikang Xia, Xiang Liu, Shutao Xia, Yong Jiang, Jianwu Lin:
Alpha Discovery Neural Network based on Prior Knowledge. CoRR abs/1912.11761 (2019) - 2018
- [j42]Xiaohu Tang, Shu-Tao Xia, Chao Tian, Qin Huang, Xiang-Gen Xia:
Special focus on distributed storage coding. Sci. China Inf. Sci. 61(10): 100300:1-100300:2 (2018) - [j41]Tao Dai, Ke Gu, Li Niu, Yong-bing Zhang, Weizhi Lu, Shu-Tao Xia:
Referenceless quality metric of multiply-distorted images based on structural degradation. Neurocomputing 290: 185-195 (2018) - [j40]Yanbo Lu, Xinji Liu, Shu-Tao Xia:
On the Single-Parity Locally Repairable Codes with Multiple Repairable Groups. Inf. 9(11): 265 (2018) - [j39]Bin Chen, Shu-Tao Xia, Jie Hao, Fang-Wei Fu:
Constructions of Optimal Cyclic (r, δ) Locally Repairable Codes. IEEE Trans. Inf. Theory 64(4): 2499-2511 (2018) - [j38]Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu:
A Novel Consistent Random Forest Framework: Bernoulli Random Forests. IEEE Trans. Neural Networks Learn. Syst. 29(8): 3510-3523 (2018) - [j37]Weizhi Lu, Tao Dai, Shu-Tao Xia:
Binary Matrices for Compressed Sensing. IEEE Trans. Signal Process. 66(1): 77-85 (2018) - [c77]Tao Dai, Yong-bing Zhang, Li Dong, Lida Li, Xin-Ji Liu, Shu-Tao Xia:
Content-Aware Bilateral Filtering. BigMM 2018: 1-6 - [c76]Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, Shu-Tao Xia:
Iterative Learning With Open-Set Noisy Labels. CVPR 2018: 8688-8696 - [c75]Zhiya Xu, Tao Dai, Li Niu, Jiawei Li, Qingtao Tang, Shu-Tao Xia:
Sure-Based Dual Domain Image Denoising. ICASSP 2018: 1418-1422 - [c74]Yang Zhang, Qingtao Tang, Li Niu, Tao Dai, Xi Xiao, Shu-Tao Xia:
Self -Paced Mixture of T Distribution Model. ICASSP 2018: 2796-2800 - [c73]Zhijie Zhu, Qing Li, Shu-Tao Xia, Mingwei Xu:
CAFFE: Congestion-Aware Fast Failure Recovery in Software Defined Networks. ICCCN 2018: 1-9 - [c72]Jiawei Li, Tao Dai, Qingtao Tang, Yeli Xing, Shu-Tao Xia:
Cyclic Annealing Training Convolutional Neural Networks for Image Classification with Noisy Labels. ICIP 2018: 21-25 - [c71]Yeli Xing, Jiawei Li, Tao Dai, Qingtao Tang, Li Niu, Shu-Tao Xia:
Portrait-Aware Artistic Style Transfer. ICIP 2018: 2117-2121 - [c70]Xingjun Ma, Yisen Wang, Michael E. Houle, Shuo Zhou, Sarah M. Erfani, Shu-Tao Xia, Sudanthi N. R. Wijewickrema, James Bailey:
Dimensionality-Driven Learning with Noisy Labels. ICML 2018: 3361-3370 - [c69]Yao Yao, Xi Xiao, Chengping Zhang, Shutao Xia:
Classifying Quality Centrality for Source Localization in Social Networks. ICWS 2018: 295-307 - [c68]Bin Chen, Shu-Tao Xia, Jie Hao, Fang-Wei Fu:
On Optimal Pseudo-cyclic ($r, \delta$) Locally Repairable Codes. ISIT 2018: 1191-1195 - [c67]Jie Hao, Yi-Xian Yang, Kenneth W. Shum, Shu-Tao Xia:
On the Maximal Code Length of Optimal Linear Locally Repairable Codes. ISIT 2018: 1326-1330 - [c66]Bin Chen, Shu-Tao Xia:
Bandwidth Efficiency of Distance-optimal Scalar Locally Repairable Codes. ITW 2018: 1-5 - [c65]Weijun Fang, Fang-Wei Fu, Bin Chen, Shu-Tao Xia:
On Optimal (r, δ)-LRCs with Length n | (q+1). ITW 2018: 1-5 - [c64]