基本信息
侯新文男硕导中国科学院自动化研究所
电子邮件： xwhou@nlpr.ia.ac.cn
通信地址： 海淀区中关村东路95号
邮政编码： 100190
部门/实验室：智能系统与工程研究中心
研究领域


模式识别、计算机视觉、深度学习、强化学习、生成对抗学习、智能博弈、人工智能的数学理论



研究经历



侯新文，2001年毕业于北京大学数学系，获理学博士学位，同年进入南开大学数学系攻读博士后，出站后任中国科学院自动化研究所模式识别国家重点实验室副研究员，现为中科院自动化所项目研究员、硕士研究生导师。本人长期从事计算机视觉和机器学习研究，在人脸识别领域提出了直接形象模型(DAM) ,在子空间学习领域提出局部化非负矩阵分解(LNMF)，在图像文字检测中提出使用条件虽机场过滤文本部件，在物体检测、运动跟踪、流形学习、AdaBoost、机器学习基础理论等方面发表过多篇文章，Google Scholar 2200多次 。近年来工作重点转向强化学习、生成对抗学习、元学习、智能博弈等通用人工智能方向，以在游戏博弈中战胜人类选手为应用目标，以提出人工智能的统一数学理论为长期研究目标。








高引用论文Google Scholar引用2200多次，其中超过100次引用的论文如下：
[1]Learning Spatially Localized, Parts-BasedRepresentation, 927次
[2]A hybrid approach to detect and localize texts in natural scene images, 367次
[3]Direct Appearance Models,219次
[4]Text localization in natural scene images based on conditional random field,144次
[5]Learning Multiview Face Subspaces and Facial Pose EstimationUsing Independent Component Analysis,112次



arxiv预印论文


Pei Yingjun, Hou Xinwen，Learning Representations in Reinforcement Learning: An Information Bottleneck Approach.https://arxiv.org/abs/1911.05695




招生信息


2019年度招收2名硕士，研究深度学习、生成对抗学习或强化学习的理论方法和应用技术




招生专业081104-模式识别与智能系统

招生方向计算机视觉
模式识别理论与方法
强化学习


教育背景1998-09--2001-06北京大学数学系博士


工作经历
工作简历2004-07~现在,中国科学院自动化研究所,副研究员
2003-12~2004-06,中科院自动化所,项目聘用
2001-07~2003-11,南开大学数学系,博士后


教授课程模式识别课


出版信息
期刊论文


















[1] 申翔翔，侯新文，尹传环，深度强化学习中状态注意力机制的研究，智能系统学报，2019.
[2]D.Wang, X. W. Hou, J. Xu, S. Yue, C.-L. Liu, Traffic sign detection using a cascade method with fast feature extraction and saliency test,IEEE Trans. Intelligent Transportation Systems, 18(12): 3290-3302, 2017.
[3]Jiang-ning Wang, Xiao-lin Chen, Xin-wen Hou, Li-bing Zhou, Chao-Dong Zhua and Li-qiang Jia,Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae), Pest Management Science, Wiley Online Library, 73(7):1511-1528, 2016.
[4]Y.-M. Zhang, K. Huang, X. Hou, C.-L. Liu, Learning locality preserving graph from data,IEEE Trans. SMC Part B, 44(11): 2088-2098, 2014.
[5]Guoqiang Zhong, Kaizhu Huang, Xinwen Hou, S. Xiang, Local Tangent Space Laplacian Eigenmaps, Computational Intelligence, 2012

[6]Y.-F. Pan, X.W.Hou, C.-L. Liu, A hybrid approach to detect and localize texts in natural scene images,IEEE Trans. Image Processing, 20(3): 800-813, 2011.
[7]张蕾,陈小琳,侯新文,刘成林,樊利民,汪兴鉴,实蝇科果实蝇属昆虫数字图像自动识别系统的构建和测试,昆虫学报，54(2):184-196,2011.
[8]X.-B. Jin, C.-L. Liu, X. W.Hou, Regularized margin-based conditional log-likelihood loss for prototype learning,Pattern Recognition, 43(7): 2428-2438, 2010.
[9]陈小琳,侯新文,刘成林,刘晓秋,张知彬，昆虫图像自动鉴别技术，昆虫知识，45(2): 317-322, 2008.

[10]W. Dong, X. Hou, J. Liu,Y. Fang, C. Jin and Q. Zhu, 3D virtual reconstruction of the pleistocene cheetah skullfrom the Tangshan, Nanjing, China, Progress In Natural Science， vol. 17(1), pp. 74-79, 2007.
[11]董为，侯新文，房迎三，刘金毅，朱奇志， 南京汤山早更新世猎豹头骨CT扫描数据的三维重建，自然科学进展，vol. 16(4), pp. 1146-1152, 2006.
[12] Stan Z. Li, X. G. Lv, X. W. Hou, X. H. Peng and Q. S. Cheng, Learning Multiview Face Subspaces and Facial Pose Estimation
Using Independent Component Analysis, IEEE Trans. Image Processing, 14(6):705- 712, 2005.
[13]Shuicheng Yan, Xinwen Hou, Stan Z. Li, Hongjiang Zhang, and Qiansheng Cheng, Face AlignmentUsing View-Based Direct Appearance Models, Special Issue on Facial Image Processing, Analysis andSynthesis, International Journal of Imaging Systems and Technology, Vol.1, p106-112, 2003.
[14]侯新文，程乾生，一种改进的变分Snake模型，数学的理论与实践，vol. 31(2), pp. 202-205, 2001.
























专著章节

[1]A. Lu, X. W.Hou, C.-L. Liu, X. Chen, Insect recognition using sparse coding and decision fusion, In:Computer Vision and Pattern Recognition in Environmental Informatics, Jun Zhou, Xiao Bai and Terry Caelli (Eds.), IGI Global, pp.124-145, 2015.



会议论文































[1]Xiangxiang Shen, Chuanhuan Yin, Yekun Chai and Xinwen Hou, Exponential Moving Averaged Q-network for DDPG, The Second China pattern recognition and computer vision Conference (PRCV), 2019.
[2]Zhunan Li and Xinwen Hou,Mixing Update Q-value for Deep Reinforcement Learning, International Joint Conference on Neural Networks(IJCNN), 2019.
[3]Xiangxiang Shen, Chuanhuan Yin, Xinwen Hou, Self-Attention for Deep Reinforcement Leraning, International Conference on Mathematics and Artificial Intelligence(ICMAI), 2019.
[4]Y. Wang, X.-Y. Zhang, Y. Zhang, X.W.Hou and C.-L Liu, Exploiting Coarse-to-Fine Mechanism for Fine-Grained Recognition,Proc. Int. Conf. Image Processing (ICIP),Phoenix, USA, September 25-28, 2016, pp.649-653.
[5]D. Wang, X. W.Hou, C.-L Liu, Traffic Sign Detection from Video: A Fast Approach with Tracking,Proc. 3rd ACPR, Kuala Lumpur, Malaysia, 2015.
[6]D. Wang, S. Yue, J. Xu, X. W.Hou, C.-L Liu, A saliency-based cascade method for fast traffic sign detection,IEEE Intelligent Vehicles Symposium, Seoul, Korea, 2015, pp.180-185.
[7]Y. Liu, X. W.Hou, C.-L. Liu, A compact spatial feature representation for image classification,Proc. 2nd ACPR, Okinawa, Japan, 2013, pp.601-605.
[8]X.-J. Jin, Q.-F. Wang, X. W.Hou, C.-L. Liu, Visual gesture character string recognition by classification-based segmentation with stroke deletion,Proc. 2nd ACPR, Okinawa, Japan, 2013, pp.120-124.
[9]Y. Liu, X.-Y. Zhang, K. Huang, X.W. Hou, C.-L. Liu, Multiple outlooks learning with support vector machines,Proc. ICONIP 2012, LNCS Vol.7665, pp.116-124.
[10]A. Lu, X. W.Hou, C.-L. Liu, X. Chen, Insect species recognition using discriminative local soft coding,Proc. 21th ICPR, Tsukuba, Japan, 2012, pp.1221-1224.
[11]Y.-F. Pan, C.-L. Liu, X. W.Hou, Fast scene text localization by learning-based filtering and verification,Proc. Int. Conf. Image Processing (ICIP), Hong Kong, 2010, pp.2269-2272.
[12]A. Lu, X.W. Hou, X. Chen, C.-L. Liu, Insect species recognition using sparse representation,Proc. BMVC 2000, Aberystwyth, UK, 2010.
[13]X.-B. Jin, X.W. Hou, C.-L. Liu, Multi-class AdaBoost with hypothesis margin,Proc. 20th ICPR, Istanbul, Turkey, 2010, pp.65-68.
[14]H. Wang, X. W.Hou, C.-L. Liu, Boosting incremental semi-supervised discriminant analysis for tracking,Proc. 20th ICPR, Istanbul, Turkey, 2010, pp.2748-2751.
[15]Y.-M. Zhang, Y. Zhang, D.-Y. Yeung, C.-L. Liu, X. W.Hou, Transductive learning on adaptive graphs,Proc.24th AAAI Conference on Artificial Intelligence, 2010,pp.661-666.
[16]G. Zhong, W.-J. Li, D.-Y. Yeung, X.W. Hou, C.-L. Liu, Gaussian process latent random field,Proc.24th AAAI Conference on Artificial Intelligence, 2010, pp.679-684.
[17]G. Zhong, X. W.Hou, C.-L. Liu, Relative distance-based Laplacian eigenmaps,Proc. 2009 Chinese Conference on Pattern Recognition (CCPR) and First CJK Workshop on Pattern Recognition (CJKPR), Nanjing, China, 2009, pp.784-788.
[18]H. Wang, X. W.Hou, C.-L. Liu,Objecttracking bybidirectionallearning withfeatureselection,ICIP2009, Cairo, Egypt, 2009.
[19]Y.-M. Zhang, X.W.Hou, S. Xiang, C.-L. Liu,Subspace regularization: a new semi-supervised learning method,ECML PKDD2009,Bled, Slovenia, LNCS Vol.5782, Springer, 2009, pp.586-601.
[20]Y.-F. Pan, X. W.Hou, C.-L. Liu, Text localization in natural scene images based on conditional random field,Proc. 10th ICDAR, Barcelona, Spain, 2009, pp.6-10.
[21]X.-B. Jin, C.-L. Liu, X.W.Hou, Prototype learning by margin-based conditional log-likelihood loss,Proc. 19th ICPR, Tampa, USA, 2008.
[22]Y.-F. Pan, X. W.Hou, C.-L. Liu, A robust system to detect and localize texts in natural scene images,Proc. 8th IAPR Int. Workshop on DAS, Nara, Japan, Sep. 2008, pp.35-42.
[23]X.-H. Liu, C.-L. Liu, X. W.Hou, A pooled subspace mixture density model for pattern classification in high-dimensional spaces,Proc. IJCNN 2008, Hong Kong, pp.2467-2472.
[24]X.-B. Jin, X. Hou, C.-L. Liu, A hybrid generative-discriminative learning algorithm for Bayesian network structure,Proc. 5^thInt. Conf. on Wavelet Analysis and Pattern Recognition, Beijing, China, 2007, Vol.2, pp.618-623.
[25]Fei Wu, Yong-Ge Wang and Xin-Wen Hou, License Plate Character Recognition Based on Framelet,Proc. 5^thInt. Conf. on Wavelet Analysis and Pattern Recognition, Beijing, China, 2007, Vol.2, pp.673-676.
[26]X. Hou, C.-L. Liu, Tieniu Tan, Learning boosted asymmetric classifiers for object detection,Proc. CVPR 2006, New York, Vol.1, pp.330-338.
[27]Y. Wang, X. W. Hou, T. N. Tan, Recognize Multi-people Interactive Activity by PCA-HMMs, the 7thAsian Conference on Computer Vision (ACCV06), Lecture Notes in Computer Science, 2006, vol. 3581, pp. 160-169.
[28]J. L. Cui, T. N. Tan, X. W. Hou, Y. H. Wang, Z. S. Wei, An Iris Detection Method Based onStructure Information, Advances in Biometric Person Authentication: International Workshop onBiometric Recognition Systems, Lecture Notes in Computer Science, 2005, vol. 3781, pp. 157-164
[29]Stan Z. Li, Xianhuan Peng, Xinwen Hou, Hongjiang Zhang and Qiansheng Cheng, Multi-view face pose estimation based on supervised ISA learning, Proceedings of th Fifth IEEE International Conference on Automatic Face and Gesture Recognition, 2002.
[30]Xinwen Hou, Stan Z. Li, Hongjiang Zhang, and Qiansheng Cheng, Direct Appearance Models, IEEE InternationalConferenceon Computer Vision and Pattern Recognition, pp.828-833, Vol 1, 2001.
[31]S. Z. Li, X. W. Hou, H. J. Zhang, Q. S. Cheng, Learning Spatially Localized, Parts-BasedRepresentation,Proceedings of IEEE International Conferenceon Computer Vision andPatternRecognition, 2001, vol. 1, pp. 207-212.
[32]S.Z. Li, J. Yan, X.W. Hou, Z.Y. Li, and H.J. Zhang, Learning Low Dimensional InvariantSignature of 3-D Object under Varying View and Illumination from 2-D Appearances, In Proceedingsof 8th IEEE International Conference on Computer Vision, Vancouver, Vol.1, pp.635–640, 2001.
[33]Weidong Sun, and Xinwen Hou, Multi-Sensor Information Synthesized Method for Cloud Clearing, Proceedings of 1997 China-Japan Symposium on Advanced Information Technology, 1997, pp. 362-367.













































科研活动
科研项目（ 1 ） 自底向上的人机对抗技术, 主持,市地级,2017-01--2019-12
（ 2 ） 人机对抗空间建模与态势认知, 参与,国家级,2016-11--2019-10
（ 3 ） 2018年人机对抗挑战赛, 参与,国家级,2018-03--2020-03
（ 4 ） 2018年人机对抗挑战赛-先知兵圣AI接口与框架开发, 主持,国家级,2018-03--2020-03