机器学习、稀疏表示及应用

[1] Dongxian Wu, Yisen Wang, Shu-Tao Xia, James Bailey, Xingjun Ma, Skip connections matter: on the transferability of adversarial examples generated with RESNETs, Proc. International Conference on Learning Representations(ICLR-20), spotlight paper, Virtual Conference, Addis Ababa, Ethiopia, Apr. 2020.

[2] Bowen Zhao, Xi Xiao, Guojun Gan, Bin Zhang, Shutao Xia, Maintaining discrimination and fairness in class incremental learning,Proc. IEEE Conference on Computer Vision and Pattern Recognition(CVPR-20), accepted, Seattle, Washington, U.S.A., Jun. 2020.

[3] 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, Proc. IEEE Conference on Computer Vision and Pattern Recognition(CVPR-20), accepted, Seattle, Washington, U.S.A., Jun. 2020.

[4] 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(NN), vol. 125, pp. 303–312, 2020.

[5] Zhendong Peng, Xi Xiao, Guangwu Hu, Arun Kumar Sangaiah, Mohammed Atiquzzaman, Shutao Xia. ABFL: an autoencoder based practical approach for software fault localization, Information Sciences (IS), vol. 510, pp. 108-121, Feb. 2020.

[6] Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, Lei Zhang. Second-order attention network for single image super-resolution,Proc. IEEE Conference on Computer Vision and Pattern Recognition(CVPR-19), oral paper, Long Beach, CA, U.S.A., Jun. 2019.

[7] Yang Bai, Yan Feng, Yisen Wang, Tao Dai, Shu-Tao Xia, Yong Jiang. Hilbert-based generative defense for adversarial examples, Proc. International Conference on Computer Vision(ICCV-19), pp. 4784-4793, Seoul, Korea, Oct.-Nov. 2019.

[8] Hongshan Li, Yu Guo, Zhi Wang, Shutao Xia, Wenwu Zhu. AdaCompress: adaptive compression for online computer vision services, Proc. the 27th ACM International Conference on Multimedia(MM-19), pp. 2440-2448, Nice, France, Oct. 2019.

[9] Xiyu Yan, Shuai Chen, Zihao He, Chunmei Li, Feng Zheng, Tao Dai, Shuo Dong, Yong Jiang, Shu-Tao Xia. Automatic grassland degradation estimation using deep learning, Proc. the 28th International Joint Conference on Artificial Intelligence(IJCAI-19), Macao, China, Aug. 2019.

[10] Xi Xiao, Rui Li, Hai-Tao Zheng, Runguo Ye, Arun KumarSangaiah, Shutao Xia, Novel dynamic multiple classification system for network traffic, Information Sciences (IS), vol. 479, pp. 526-541, 2019.

[11] Jin-Yuan Chen, Hai-Tao Zheng, Yong Jiang, Shu-Tao Xia, Cong-Zhi Zhao. A probabilistic model for semantic advertising,Knowledge and Information Systems(KIS), vol. 59, pp. 387-412, May 2019.

[12] Weizhi Lu, Weiyu Li, Wei Zhang, and Shu-Tao Xia. Expander recovery performance of bipartite graphs with girth greater than 4,IEEE Transactions on Signal and Information Processing over Networks, pp. 418-427, vol. 5, no. 3, Sep. 2019.

[13] Songtao Wang, Dan Li, Yang Cheng, Jinkun Geng, Yanshu Wang, Shu-Tao Xia and Jianping Wu. BML: a high-performance, low-cost gradient synchronization algorithm for DML training, Proc. Neural Information Processing Systems(NIPS-18), Montreal, Canada, Dec. 2018.

[14]Xingjun Ma, Yisen Wang, Michael E. Houle, Shu-Tao Xia, James Bailey. Dimensionality-driven learning with noisy labels,Proc. the Thirty-fifth International Conference on Machine Learning(ICML-18), long talk, Stockholm, Sweden, Jul. 2018.

[15]Yisen Wang, Weiyang Liu, Xingjun Ma, James Bailey, Hongyuan Zha, Le Song, and Shu-Tao Xia. Iterative learning with open-set noisy labels, Proc. IEEE Conference on Computer Vision and Pattern Recognition(CVPR-18), spotlight paper, Salt Lake City, U.S.A., Jun. 2018.

[16]Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, Xingquan Zhu. A novel consistent random forests framework: Bernoulli random forests.IEEE Transactions on Neural Networks and Learning Systems(TNNLS), vol. 29, no. 8, pp. 3510-3523, Aug. 2018.

[17]Rui Li, Xi Xiao, Shiguang Ni, Haitao Zheng, Shutao Xia, Byte segment neural network for network traffic classification,Proc. IEEE/ACM International Symposium on Quality of Service(IWQoS-18), Banff, Alberta, Canada, Jun. 2018.

[18]Weizhi Lu, Tao Dai, Shu-Tao Xia. Binary matrices for Compressed Sensing, IEEE Transactions on Signal Processing(TSP), vol. 66, no. 1, pp. 77-85, Jan. 2018.

[19]Chaobing Song, Shaobo Cui, Yong Jiang, Shu-Tao Xia. Accelerated stochastic greedy coordinate descent by soft thresholding projection onto simplex. Proc. Neural Information Processing Systems(NIPS-17), spotlight paper, Long Beach, U.S.A., Dec. 2017.

[20]Qingtao Tang, Tao Dai, Li Niu, Yisen Wang, Shu-Tao Xia, and Jianfei Cai. Robust Survey Aggregation with Student-t Distribution and Sparse Representation. Proc. the 26th International Joint Conference on Artificial Intelligence(IJCAI-17), pp. 2829-2835, Melbourne, Australia, Aug. 2017.

[21]Qingtao Tang, Li Niu, Yisen Wang, Tao Dai, Wangpeng An, Jianfei Cai, Shu-Tao Xia. Student-t Process Regression with Student-t Likelihood. Proc. the 26th International Joint Conference on Artificial Intelligence(IJCAI-17), pp. 2822-2828, Melbourne, Australia, Aug. 2017.

[22]Xin-Ji Liu, Shu-Tao Xia, and Fang-Wei Fu, Reconstruction guarantee analysis of basis pursuit for binary measurement matrices in compressed sensing, IEEE Transactions on Information Theory (TIT), vol. 63, no. 5, pp. 2922-2932, May 2017.

[23]Y. Wang, S. Romano, N.X. Vinh, J. Bailey, X. Ma, S.-T. Xia. Unbiased multivariate correlation analysis, Proc. the 31st AAAI Conference on Artificial Intelligence(AAAI-17), San Francisco, California, U.S.A., Feb. 2017.

[24]Yisen Wang, Fangbing Liu, Shu-Tao Xia, Jia Wu. Link sign prediction by variational Bayesian probabilistic matrix factorization with student-t prior, Information Sciences (IS), vol. 405, pp. 175-189, 2017.

[25]Yisen Wang, Shu-Tao Xia, and Jia Wu, A less-greedy two-term Tsallis Entropy Information Metric approach for decision tree classification, Knowledge-Based Systems (KBS), vol. 120, pp. 34-42, Mar. 2017.

[26]Weizhi Lu, Tao Dai, and Shu-Tao Xia, Compressed Sensing Performance of Binary Matrices with Binary Column Correlations, Proc. 2017 Data Compression Conference(DCC-17), pp. 151-160, Snowbird, Utah, U.S.A., Apr. 2017.

[27]Yisen Wang, Qingtao Tang, Shu-Tao Xia, Jia Wu, Xingquan Zhu, Bernoulli random forests: closing the gap between theoretical consistency and empirical soundness, Proc. the 25th International Joint Conference on Artificial Intelligence(IJCAI-16), pp. 2167-2173, New York, U.S.A., Jul. 2016.

[28]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, vol. 290, pp. 185-195, May 2018.

[29]Tao Dai, Weizhi Lu, Wei Wang, Jilei Wang, and Shu-Tao Xia, Entropy-based bilateral filtering with a new range kernel,Signal Processing, vol. 137, pp. 223-234, Aug. 2017.

[30] S.-T. Xia, X.-J. Liu, Y. Jiang, and H.-T. Zheng, Deterministic constructions of binary measurement matrices from finite geometry,IEEE Transactions on Signal Processing (TSP), vol. 63, no. 4, pp. 1017-1029, Feb. 2015.

[31]C.-B. Song and S.-T. Xia, Sparse signal recovery by l_q minimization under restricted isometry property, IEEE Signal Processing Letters (SPL), vol. 21, no. 9, pp. 1154-1158, Sep. 2014.

[32] C.-B. Song, S.-T. Xia, and X.-J. Liu, Improved analysis for subspace pursuit algorithm in terms of restricted isometry constant, IEEE Signal Processing Letters (SPL), vol. 21, no. 11, pp. 1365-1369, Nov. 2014.

[33]F. Zhou, S.-T. Xia, and Q. Liao. Nonlocal pixel selection for multisurface fitting-based super-resolution. IEEE Transactions on Circuits and systems for video technology (TCSVT), vol. 24, no.12, pp. 2013-2017, Dec. 2014.

信息论编码及网络

[34]Bin Chen, Weijun Fang, Shu-Tao Xia, and Fang-Wei Fu. Constructions of optimal (r,δ) locally repairable codes via constacyclic Codes, IEEE Transactions on Communications (TCOM) , pp. 5253-5263, vol. 67, no. 8, Aug. 2019.

[35]Bin Chen, Shu-Tao Xia, Jie Hao, and Fang-Wei Fu. Constructions of optimal cyclic (r,δ) locally repairable codes,IEEE Transactions on Information Theory (TIT), vol. 64, no. 4, pp. 2499-2511, Apr. 2018.

[36]Xi Xiao, Peng Fu, Changsheng Dou, Qing Li, Guangwu Hu, and Shutao Xia. Design and analysis of SEIQR worm propagation model in mobile internet, Communications in Nonlinear Science and Numerical Simulation,vol. 43,pp. 341-350,Feb. 2017.

[37] Qing Li, Mingwei Xu, Qi Li, Dan Wang, Yong Jiang, Shu-Tao Xia, Qingmin Liao. Scale the Internet routing table by generalized next hops of strict partial order, Information Sciences (IS), vol. 412, pp. 101-115, Oct. 2017.

[38] Yong Cui,Lian Wang,Xin Wang,Yisen Wang,Fengyuan Ren,Shutao Xia. End-to-end coding for TCP,IEEE Network, vol. 30, no. 2, pp. 68-73, Mar. 2016.

[39] Y. Jiang, S.-T. Xia,and F.-W. Fu. Stopping set distributions of some kinds of Reed-Muller codes,IEEE Transactions on Information Theory (TIT), vol. 57, no. 9, pp. 6078-6088, Sep. 2011.

[40] S.-T. Xia and F.-W. Fu, Minimum pseudo-weight and minimum pseudo-codewords of LDPC Codes, IEEE Transactions on Information Theory (TIT), vol. 54, no. 1, pp. 480-485, Jan. 2008.

[41] S.-T. Xia, F.-W. Fu, and S. Ling, A lower bound on the probability of undetected error for binary constant weight codes. IEEE Transactions on Information Theory (TIT), vol. 52, no. 9, pp. 4235-4243, Sep. 2006.

[42] S.-T. Xia, F.-W. Fu, Y. Jiang, and S. Ling, The probability of undetected error for binary constant weight codes. IEEE Transactions on Information Theory (TIT), vol. 51, no. 9, pp. 3364-3373, Sep. 2005.

[43] F.-W. Fu, T. Klove, and S.-T. Xia, The undetected error probability threshold of m-out-of-n codes, IEEE Transactions on Information Theory (TIT), vol.46, no.4, pp.1597-1599, Jul. 2000.

[44] F.-W. Fu and S.-T. Xia, Binary constant weight codes for error detection, IEEE Transactions on Information Theory (TIT), vol. 44, no. 3, pp. 1294-1299, May 1998.

[45] S.-T. Xia and F.-W. Fu, Johnson type bounds on constant dimension codes. Designs, Codes and Cryptography,vol.50, no.2, pp. 163-172, 2009.

[46] S.-T. Xia and F.-W. Fu, Undetected error probability of q-ary constant weight codes. Designs, Codes and Cryptography,vol. 48, pp. 125-140, 2008.

[47] F.-W. Fu and S.-T. Xia, The characterization of binary constant weight codes meeting the bound of Fu and Shen,Designs, Codes and Cryptography,vol.43, pp. 9-20, 2007.

[48] S.-T. Xia, F.-W. Fu, and Y. Jiang, On the minimum average distance of binary constant weight codes, Discrete Mathematics,vol. 308, pp. 3847-3859, 2008.

[49] S.-T. Xia and F.-W. Fu, On the average Hamming distance for binary codes. Discrete Applied Mathematics, vol. 89, pp. 269-276, 1998.

[50] 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-20, accepted, Los Angeles, USA, Jun. 2020.

[51] Weijun Fang, Bin Chen, Shu-Tao Xia, Fang-Wei Fu, Perfect LRCs and k-optimal LRCs, ISIT-20, accepted, Los Angeles, USA, Jun. 2020.

[52] 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-20, accepted, Los Angeles, USA, Jun. 2020.

[53]Xiaoteng Ma, Qing Li, Jimeng Chai, Xi Xiao, Shu-tao Xia, Yong Jiang. Steward: smart edge based joint QoE optimization for adaptive video streaming. Proc. the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video(NOSSDAV-19), pp. 31-36, Amherst, MA, USA, Jun. 2019.

[54]Jie Hao, Kenneth W. Shum, Shu-Tao Xia, Yi-Xian Yang. Classification of optimal ternary (r,\delta)-locally repairable codes attaining the Singleton-like bound, Proc. IEEE International Symposium on Information Theory(ISIT-19), pp. 2828-2832, Vail, Paris, France, Jul. 2019.

[55]Bin Chen, Shu-Tao Xia, Jie Hao. Improved bounds and optimal constructions of locally repairable codes with distance 5 and 6, Proc. IEEE International Symposium on Information Theory(ISIT-19), pp. 2823-2827, Vail, Paris, France, Jul. 2019.

[56]Bin Chen, Shu-Tao Xia, Jie Hao, and Fang-Wei Fu, On optimal pseudo-cyclic (r,δ) locally repairable codes,Proc. IEEE International Symposium on Information Theory(ISIT-18), pp. 1191-1195, Vail, Colorado, USA, Jun. 2018.

[57]Jie Hao, Kenneth W. Shum, Shu-Tao Xia, and Yixian Yang, On the maximal code length of optimal linear locally repairable codes, Proc. IEEE International Symposium on Information Theory(ISIT-18), pp. 1326-1330, Vail, Colorado, USA, Jun. 2018.

[58]Jie Hao, Shu-Tao Xia, and Bin Chen, On optimal ternary locally repairable codes, Proc. IEEE International Symposium on Information Theory(ISIT-17), pp. 171-175, Aachen, Germany, Jun. 2017.

[59]Bin Chen, Shu-Tao Xia, and Jie Hao, Locally repairable codes with multiple (ri, δi)-localities, Proc. IEEE International Symposium on Information Theory(ISIT-17), pp. 2038-2042, Aachen, Germany, Jun. 2017.

[60]J. Hao, S.-T. Xia, and B. Chen, Some results on optimal locally repairable codes, Proc. IEEE International Symposium on Information Theory(ISIT-16), pp. 440-444, Barcelona, Spain, Jul. 2016.

[61]J. Hao, S.-T. Xia, and B. Chen, Recursive bounds for locally repairable codes with multiple repair groups, Proc. IEEE International Symposium on Information Theory(ISIT-16), pp. 645-649, Barcelona, Spain, Jul. 2016.