近期论文
查看导师最新文章
（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）
[*] Chao Li, Yixiao Yang, Kun He*, Stephen Lin, John Hopcroft. Single Image Reflection Removal through Cascaded Refinement, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020).
[*]Jiadong Lin, Chuanbiao Song, Kun He*, Liwei Wang, John Hopcroft. Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks, Eighth International Conference on Learning Representations (ICLR 2020) .
[*] Chuanbiao Song, Kun He*, Jiadong Lin, Liwei Wang, John Hopcroft. Robust Local Features for Improving the Generalization of Adversarial Training, Eighth International Conference on Learning Representations (ICLR 2020).
[*] Shuhuai Ren, Yihe Deng, Kun He*, Wanxiang Che. Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency. 1085-1097, Proceedings of the 57th Conference of the Association for Computational Linguistics (ACL 2019), July 29-31, 2019, Florence, Italy.
[*] Chuanbiao Song, Kun He*, Liwei Wang, John Hopcroft. Improving the Generalization of Adversarial Training with Domain Adaptation. ICLR 2019, New Orleans, Louisiana, May 2019.
[*] Liwei Wang, Lunjia Hu, Jiayuan Gu, Zhiqiang Hu, Yue Wu, Kun He, John Hopcroft. Towards Understanding Learning Representations: To What Extent Do Different Neural Networks Learn the Same Representation. In: 31th Annual Conference on Neural Information Processing Systems (NeurIPS 2018), Spotlight paper, Canada, 2018.
[*] Kun He, Yan Wang, John Hopcroft. A Powerful Generative Model Using Random Weights for the Deep Image Representation. In: : 29th Annual Conference on Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, pp. 631-639, Dec. 2016.
[*] John E. Hopcroft，Kun He. Computer Science in the Information Age, IEEE Intelligent Informatics Bulletin, vol. 18(2): 3-6, 2017.
[*] Hongfei Wang, Jiangwen Li, and Kun He*. Hierarchical Ensemble Reduction and Learning for Resource-Constrained Computing. ACM Transactions on Design Automation of Electronic Systems（TODAES）, vol. 9, No. 4, Article 39. 2020.
[*] Hongfei Wang, Kun He*. Improving Test and Diagnosis Efficiency through Ensemble Reduction and Learning. ACM Transactions on Design Automation of Electronic Systems （TODAES）vol. 25(4): 49, 2019.
[*] Hongfei Wang, Kun He*. Sub-population prediction using enhanced correlation filters. Electronics Letters , vol. 54 (13): 831 - 833, 2018.
[*] Hongfei Wang, Jianwen Li, Kun He*, Wenjie Cai. Hierarchical ensemble learning for resource-aware FPGA computing: work-in-progress, CODES+ISSS, 2018.
[*] Jialu Bao, Kun He*, Xiaodong Xin, Bart Selman, John Hopcroft. Hidden Community Detection on Two-layer Stochastic Models: a Theoretical Perspective. In: 16th Annual Conference on Theory and Applications of Models of Computation (TAMC), 2020.
[*] Kun He, Pan Shi*, David Bindel, John Hopcroft. Krylov Subspace Approximation for Local Community Detection in Large Networks. ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 13(5): 52, 2019.
[*] Zengjian Chen, Jiayi Liu, Yihe Deng, Kun He*, John Hopcroft. Adaptive Wavelet Clustering for High Noise Data. ICDE 2019, April 8-12. Macau, China.
[*] Kun He, Wu Wang, Xiaosen Wang, John E. Hopcroft. Anchor Word Selection for Separable Topic Discovery based on Word Co-occurrence Probability. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (Wiley DMKD), e1313, 2019.
[*] Pan Shi, Kun He*, David Bindel, John Hopcroft. Locally-biased Spectral Approximation for Community Detection. Knowledge-Based Systems (KBS), vol. 164: 459-472, 2019.
[*] Dany Kamuhanda, Kun He*. A Nonnegative Matrix Factorization Approach for Multiple Local Community Detection, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018, Barcelona, Spain.
[*] Kun He, Yingru Li, Sucheta Soundarajan, John E. Hopcroft. Hidden Community Detection in Social Networks. Information Sciences (INS), vol. 425: 92-106, 2018.
[*] Yuzhe Ma, Kun He*, John E. Hopcroft, Pan Shi. Neighbourhood Preserving Dimension Reduction via Localised Multidimensional Scaling. Theoretical Computer Science (TCS), vol. 734: 58-71, 2018.
[*] Yixuan Li, Kun He*, Kyle Kloster, David Bindel, John E. Hopcroft. Local Spectral Clustering for Overlapping Community Detection, IEEE Transactions on Knowledge Discovery from Data (TKDD), 12 (2):17, 2018.
[*] Pan Shi, Kun He*, David Bindel, John E. Hopcroft. Local Lanczos Spectral Approximation for Membership Identification. 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), Skopje, Macedonia, September 18-22, 2017.
[*] Kun He, Pan Shi, John E. Hopcroft and David Bindel. Local Spectral Diffusion for Robust Community Detection,In: the Workshop on Mining and Learning with Graphs at KDD (SIGKDD MLG'16) , SFO, CA, USA, August 2016.
[*] Yuzhe Ma, Kun He*, John E. Hopcroft, Pan Shi. Nonlinear dimension reduction by local multidimensional scaling. In: 10th International Frontiers of Algorithmics Workshop (FAW2016), pp.158-171, Shandong, China, 2016.
[*] Kun He, Yiwei Sun, David Bindel, John Hopcroft, Yixuan Li. Detecting Overlapping Communities from Local Spectral Subspaces, 15th IEEE International Conference on Data Mining (ICDM2015), Atlantic City, USA, pp. 769-774, 2015.
[*] Yixuan Li, Kun He*, David Bindel, John E. Hopcroft. Uncovering the Small Community Structure in Large Networks, In: 24th International Conference on World Wide Web (WWW2015), Florence, Italy, pp. 658-668, 2015.
[*] Kun He, Sucheta Soundarajan, Xuezhi Cao, John E. Hopcroft, Menglong Huang: Revealing Multiple Layers of Hidden Community Structure in Networks. CoRR abs/1501.05700 (2015)
[*] Yan-Li Liu, Chu-Min Li, Hua Jiang*, Kun He*. A Learning based Branch and Bound for Maximum Common Subgraph related Problems, AAAI 2020, New York.
[*] Kun He, Huan Yang, Yan Jin*, Qian Hu, Pengli Ji. The Orthogonal Packing and Scheduling Problem: Model, Heuristic and Benchmark. IEEE Transactions on Systems, Man, and Cybernetics: Systems (TSMC), 2017.10 accepted. Page 1-12, DOI: 10.1109/TSMC.2017.2768072.
[*] Kun He, Xiaozhu Meng, Zhizhou Pan, Ling Yuan, Pan Zhou. A Novel Task-Duplication based Clustering Algorithm for Heterogeneous Computing Environments, IEEE Transactions on Parallel and Distributed Systems(TPDS), vol.30 (1):2-14, 2019.
[*] Zhen-Xing Xu, Kun He*, Chu-Min Li*. An Iterative Path-Breaking Approach with Mutation and Restart Strategies for the MAX-SAT Problem. Computers & Operations Research (COR), vol. 104, pp. 49-58, 2019.
[*] Kun He, Hui Ye*, Zhengli Wang*, Jingfa Liu. An Efficient Quasi-physical Quasi-human Algorithm for Packing Equal Circles in a Circular Container. Computers & Operations Research(COR), vol. 92, pp. 26-36, 2018.
[*] Jingfa Liu, Huiyun Zhang, Kun He, Shengyi Jiang. Multi-objective particle swarm optimization algorithm based on objective space division for the unequal-area facility layout problem. Expert System and Application (ESA), 102: 179-192 (2018).
[*] Zhizhong Zeng, Xinguo Yu, Kun He*, Zhanghua Fu. Adaptive Tabu Search and Variable Neighborhood Descent for Packing Unequal Circles into a Square. Applied Soft Computing (ASC), vol. 65, 196-213, 2018.
[*] Kun He, Mohammed Dosh*, Yan Jin, Shenghao Zou. Packing Unequal Circles into a Square Container based on the Narrow Action Spaces, SCIENCE CHINA Information Sciences(SCIS), vol.61(4): 048104, 2018.
[*] Pengli Ji, Kun He*, Yan Jin, Hongsheng Lan, Chu-Min Li. An iterative merging algorithm for soft rectangle packing and its extension for application of fixed-outline floorplanning of soft modules, Computers & Operations Research(COR), vol. 86:110-123, 2017.
[*] Jingfa Liu, Dawen Wang, Kun He, Yu Xue. Combining Wang-Landau sampling algorithm and heuristics for solving the unequal-area dynamic facility layout problem. European Journal of Operational Research (EJOR), vol. 262(3), pp. 1052-1063, 2017.
[*] Zhizhong Zeng, Xinguo Yu, Kun He*, Wenqi Huang, Zhanghua Fu. Iterated Tabu Search and Variable Neighborhood Descent for Packing Unequal Circles into a Circular Container, European Journal of Operational Research(EJOR), vol. 250(2): 615-627, 2016.
[*] Kun He, Menglong Huang, Chenkai Yang. An action space based global optimization algorithm for packing circles into a square container, Computers & Operations Research (COR), vol. 58: 67-74, 2015.
[*] Kun He, Pengli Ji, Chumin Li. A dynamic reduction algorithm for the rectangle packing area minimization problem. European Journal of Operational Research(EJOR), vol.241(3):674–685, 2015.
[*] Kun He, Danzeng Mo, Tao Ye, Wenqi Huang. A coarse-to-fine quasi-physical optimization method for solving the circle packing with equilibrium constraints problem. Computers and Industrial Engineering (CIE), vol. 66(4): 1049-1060, 2013.
[*] Wenqi Huang, Kun He*. On the weak computability of a four-dimensional orthogonal packing and time scheduling problem. Theoretical Computer Science (TCS), vol. 501(27): 1–10, 2013.
[*] Kun He, Yan Jin, Wenqi Huang. Heuristics for two-dimensional strip packing problem with 90° rotations. Expert Systems with Applications (ESA), vol. 40(14): 5542–5550, 2013.
[*] Kun He, Wenqi Huang, Yan Jin, An efficient deterministic heuristic for two-dimensional rectangular packing, Computers & Operations Research (COR), vol. 39(7): 1355-1363, 2012.
[*] Kun He, Wenqi Huang, An efficient placement heuristic for three-dimensional rectangular packing, Computers & Operations Research (COR), vol. 38(1): 227-233, 2011.
[*] Kun He, Wenqi Huang, A caving degree based flake arrangement approach for the container loading problem, Computers & Industrial Engineering (CIE), vol. 59(2), 2010: 344-351.
[*] Kun He, Wenqi Huang, Solving the single container loading problem by a fast heuristic method, Optimization Methods and Software (OMS), vol. 25(2), 2010: 263-277.
[*] Kun He, Wenqi Huang, A quasi-human algorithm for solving the three-dimensional rectangular packing problem, Science in China F: Information Sciences(SCIS), vol. 53(12), 2010: 2389-2398.
[*] Wenqi Huang, Kun He*, A caving degree approach for the single container loading problem, European Journal of Operational Research (EJOR), vol. 196(7), 2009: 93-101.
[*] Wenqi Huang, Kun He*, A new heuristic algorithm for cuboids packing with no orientation constraints, Computers & Operations Research (COR), vol. 36(2), 2009: 425-432.
[*] Wenqi Huang, Kun He*, A pure quasi-human algorithm for solving the cuboid packing problem, Science in China F: Information Sciences (SCIS), vol. 52(1), 2009: 52-58.
[*] Kun He, Yong Zhao, Clustering and scheduling method based on task duplication, Wuhan University Journal of Natural Sciences (SCIS), vol. 12(2): 260-266, 2007.
[*] Yanli Liu, Chumin Li, Kun He*, and Yi Fan. Breaking Cycle Structure to Improve Lower Bound for Max-SAT. In: 10th International Frontiers of Algorithmics Workshop (FAW'16), pp.111-124, Shandong, China, 2016.
[*] 何琨*,杨辰凯,黄梦龙,黄文奇.基于动作空间的带平衡约束圆形Packing问题的拟物求解算法, 软件学报, vol. 27(9): 2218-2229, 2016.
[*] 熊新生, 何琨*, 赵勇. 弱偏好序下存在租客的房屋匹配问题的机制设计,中国科学:信息科学, 2014, 45(9): 1140-1155.
[*] 何琨, 黄文奇, 三维矩形Packing问题的拟人求解算法, 中国科学(F辑), vol. 40(12): 1586-1595, 2010.
[*] 黄文奇, 何琨*, 求解长方体Packing问题的纯粹拟人算法, 中国科学(F辑), vol. 39(6): 617-622, 2009.
[*] 何琨, 黄文奇, 基于动作空间的三维装箱问题的确定性高效率求解算法, 计算机学报, vol. 37(8): 1786 - 1793, 2014.
[*] 何琨, 莫旦增, 许如初, 黄文奇. 基于粗精调技术的求解带平衡约束圆形Packing问题的拟物算法, 计算机学报, vol. 36(6): 1224-1234, 2013.
[*] 黄文奇, 何琨*. 四维时空高效利用的装箱调度问题及其可计算性证明. 计算机学报, vol.36(9): 1880-1888, 2013.
[*] 刘燕丽, 李初民, 何琨. 基于优化冲突集提高下界的MAXSAT完备算法, 计算机学报, vol.36(10):2087-2095, 2013. (2013 CCF中国计算机大会会议论文及优秀海报)
[*] 何琨, 赵勇, 黄文奇, 基于任务复制的分簇与调度算法, 计算机学报, vol. 31(5): 733-740, 2008.
[*] 何琨, 姬朋立, 李初民. 求解二维矩形Packing面积最小化问题的动态归约算法, 软件学报, 24(9): 2078-2088, 2013.
[*] 何琨, 黄文奇, 金燕. 基于动作空间的求解二维矩形Packing问题的高效启发式算法, 软件学报,vol.23(5):1037-1044 , 2012.(EI刊源)
[*] 何琨, 黄文奇, 求解长方体Packing问题的捆绑穴度算法, 软件学报, vol. 22(5): 843-851, 2011.(EI)
[*] 何琨, 蒋洪波. 重要的是你曾经让别人的世界更美好——访ACM图灵奖得主约翰霍普克洛夫特教授, 中国计算机学会通讯, 2016年第4期.
京公网安备 11010802027423号