Current Vitae of Yu-Hong DaiPersonal Data

Family Name: DAIGiven Name: Yu-HongBirthplace: LianYuan, HuNanBirthdate: August 28, 1971Nationality: Chinese

Basic InformationPOSITION Feng Kang Chair Professor

State Key Laboratory of Scientific and Engineering ComputingInstitute of Comput. Math. and Sci./Engr. ComputingAcademy of Mathematics and Systems Science (AMMS)Chinese Academy of Sciences

POSTAL ADDRESS No. 55, ZhongGuanCun East RoadSouth Bldg., Academy of Mathematics and Systems ScienceP. O. Box 2719, Beijing 100190, P. R. ChinaTel: +86-10-8254-1912Fax: +86-10-6254-5820Email: dyh@lsec.cc.ac.cnwww: http://lsec.cc.ac.cn/˜dyh

Research Interests with Highlights• Continuous Optimization

– Proposed the Dai-Yuan nonlinear conjugate gradient method– Solved the most fundamental question on the convergence of the BFGS method– Proposed the Dai-Fletcher (spectral gradient) method after hard analysis

• Integer Programming– Solved the open question by Nemhauser et al. (1999) on the complexity of PLCI

• Applied Optimization– Provided good theoretical and numerical analysis for an MIMO problem, receiving

best paper award of ICC2011 (a flagship conference of IEEE on Signal Processing)

Current Major Duties• Vice President, Operations Research Society of China• General Secretary, The 24th International Symposium on Mathematical Programming

(ISMP2021)• Director, Center for Optimization and Applications, AMMS, Chinese Academy of Sci-

ences

EducationPH.D. STUDY Institute of Computational Mathematics and Scientific

Engineering Computing, Chinese Academy of SciencesJuly 1994-June 1997 (under Professor Ya-xiang Yuan), Received Ph.D.

GRADUATE Computing Center, Chinese Academy of SciencesSeptember 1992 - July 1994 under Professor Ya-xiang Yuan. Transferred to a Ph.D. student

UNDERGRADUATE Dept. of Applied Mathematics, Beijing Institute of TechnologySeptember 1988 - July 1992 Beijing, China, Received B.Sc.

Working ExperiencesFENG KANG CHAIR Academy of Mathematics and Systems Science

PROFESSOR(Since 2014) Chinese Academy of Sciences

PROFESSOR Academy of Mathematics and Systems Science(Since Feb. 2006) Chinese Academy of Sciences

ASSOCIATE PROFESSOR Academy of Mathematics and Systems Science(Dec. 1998-Jan. 2006) Chinese Academy of Sciences

ASSISTANT PROFESSOR Institute of Computational Mathematics and Scientific/(Jul. 1997- Nov. 1998) Engeering Computing, Chinese Academy of Sciences

Awards and Prizes2018 “The 1st Xiao Shutie Applied Mathematics Prize”2017 “The 16th Shiing-Shen Chern Mathematics Award”2017 “National Leading Talents in Scientific and Tech. Innovation”2016 “Semi-Plenary Talk, The 5th Int. Conf. on Continuous Optim.”2015 “The 11th Feng Kang Scientific Computing Prize”2014 “Feng Kang Chair Professor”, awarded by AMMS, Chinese Academy

of Science2012 “Outstanding Scientific Research Award”, awarded by AMMS, Chinese

Academy of Science2011 The China National Funds for Distinguished Young Scientists.

2010-2011 “Numerical Methods for Nonlinear Optimization” , Excellence Course,Nov. 6, 2011

2011 Best Paper Award, International Conference on Communica-tions, Japan(with Y.F.Liu and Z.Q.Luo)

2009 Best Paper Award of Systems Science from 1979 to 20092007 The 10th Science and Technology Award for Chinese Youth.2006 Second Class Prize of The Chinese National Wards for Natural

Sciences (with Y. Yuan))2004 The Humboldt Research Fellowship.2001 Excellent Lecture Award of Graduate University of the Chinese Academy

of Sciences.1998 Zhong Jia-Qing Mathematics Award, Awarded by The Chinese

Mathematics Society, Beijing.1997 Excellent Director Scholarship of Chinese Academy of Sciences, Beijing,

Some Major Academic VisitsSept. 27 - October 3, 2019 Department of Mathematics, Linkoping University

(Joint research, invited by Oleg Burdakov)

Aug. 2014 - Sep. 2014 School of Civil and Environmental Engineering, Cornell University(As visiting professor, cooperated with C. S. Shoemaker)

Jan. 2014 - Dec. 2004 Department of Mathematics, University of Bayreuth, Germany(as a Humboldt research fellow, cooperated with K. Schittkowski)

May 2002 - April 2003 Department of Mathematics, University of Dundee, UK(cooperated with R. Fletcher under EPRSC)

July 1997 - Oct. 1997 DAMPT, Cambridge University, UK(invited by M. J. D. Powell)

Invited Talks and Memorial Talks• International Conference on Numerical Optimization and Numerical Linear Algebra,

Shangrao, Jiangxi, April 15-18, 2019 (Plenary Talk)• The XII Brazilian Workshop on Continuous Optimization, Foz Do Iguacu, Brazil, July

22-28, 2018 (Plenary Talk)• The 15th EUROPT Workshop on Advances in Continuous Optimization, Montreal,

Canada, July 12-15, 2017 (Memorial Talk to memorize Roger Fletcher)• The Fourth International Conference on Numerical Analysis and Optimization, Muscat,

Oman, January 2-5, 2017 (Invited Talk)• The 5th International Conference on Continuous Optimization 2016, Japan, Tokyo, Au-

gust 6-11, 2016 (Semi-Plenary Talk).• International Conference on Optimization, Sparsity and Adaptive Data Analysis, Beijing,

March 18-22, 2015 (Invited Talk).• The Fourth Sino-Brazil Conference on Scientific Computing, Xi’an, Sep. 22-26, 2015

(Invited Talk).• Nanjing International Conference on Numerical Optimization with Applications. Nan-

jing, Dec. 27-29, 2015 (Invited Talk).• The 10th Annual Meeting of China Society for Computational Mathematics, Guangzhou,

Sep. 18-22, 2015 (Plenary Talk).• The 2014 International Conference on Tensors and Matrices and Their Applications,

Suzhou, Dec. 16-19, 2014 (Invited Talk)• 2014 SIAM Conference on Optimization, San Diego, USA, May 19-22, 2014• The Third International Conference on Numerical Analysis and Optimization, Muscat,

Oman, Jan. 5-9, 2014 (Invited Talk)• The 9th Annual Meeting of Operations Research Society of China, Shenyang, October

19-22, 2012 (Plenary Talk)• International Conference on the Spectral Theory of the Tensor, Tianjin, May 30-June 2,

2012 (Invited Talk)• The 5th Sino-Japan Optimization Meeting, Beijing, September 26-29, 2011 (Invited Talk)• The 2nd International Conference on Numerical Analysis and Optimization, Muscat,

Sultanate of Oman, January 3-6, 2011 (invited Talk)

• The 1st International Workshop on Optimization and Regularization for ComputationalInverse Problems and Applications, Beijing, China, July 21-26, 2008 (Invited Talk)

• The 1st International Conference on Numerical Analysis and Optimization, Muscat,Sultanate of Oman, April 6-9, 2008 (invited Talk)

• The 3rd China-Australlia Workshop on Optimization: Theory, Methods and Applica-tions, Changhai, China, December 16-19, 2007 (Invited Talk)

• The 5th International Conference on Numerical Linear Algebra and Optimization, Lhasa,China, August 8-12, 2005 (Invited Talk)

• International Conference: Multiscale Optimization Methods and Applications, Florida,USA, February 26-28, 2004 (Invited by W. Hager)

• Department of Mathematics, University of Modena, Italy, September 2004 (Invited byL. Zanni)

• Department of Mathematics and Statistics, University of Edinburgh, UK, December 2002(Invited by K. Mckinnon)

• Department of Mathematical Sciences, University of Liverpool, UK, November 2002(Invited by K. Chen)

• Department of Mathematics, The Chinese University of Hong Kong, December 2001(Invited by J. Zou)

• ’01 International Conference on Numerical Optimization and Numerical Linear Algebra,Dunhuang, China, May 17-20, 2001 (Invited Talk)

• Department of Applied Mathematics, University of Campinas, Brazil, August 2001 (In-vited by J. M. Martinéz)

Organized and Joined International Conferences• International Conference on Numerical Optimization and Numerical Linear Algebra,

Shangrao, Jiangxi, April 15-18, 2019 (http://lsec.cc.ac.cn/̃ icnonla19/)• International Workshop on Modern Optimization and Applications (MOA 2018), Beijing,

June 16-18, 2018.• International Conference on Numerical Optimization and Numerical Linear Algebra,

Yinchuan, Ningxia, August 8-11, 2017 (http://lsec.cc.ac.cn/̃ icnonla17/)• International Workshop on Modern Optimization and Applications (MOA 2018), Beijing,

June 27-29, 2016.• International Conference on Numerical Optimization and Numerical Linear Algebra,

Yanan, Shaanxi, August 5-8, 2015 (http://lsec.cc.ac.cn/̃ icnonla15/index.htm)• International Conference on Numerical Optimization and Numerical Linear Algebra,

Changchun, Jilin, September 12-15, 2013 (http://lsec.cc.ac.cn/̃ icnonla13/)• The Second Sino-German Workshop on Optimization, Modeling, Methods and Applica-

tions in Industry and Management, Berlin, September 23-27, 2012.• International Conference on Numerical Optimization and Numerical Linear Algebra,

Xiamen, Fujian, November 7-11, 2011 (http://lsec.cc.ac.cn/̃ icnonla11/index.htm)• Sino-German Workshop on Optimization, Modeling, Methods and Applications in In-

dustry and Management (SGWO2011), Berlin, August 15-19, 2011.• International Conference on Numerical Optimization and Numerical Linear Algebra, Li-

jiang, Yunnan, August 16-19, 2009 (http://lsec.cc.ac.cn/̃ optim/ICNONLA09/index.htm)• International Conference on Numerical Optimization and Numerical Linear Algebra,

Urumqi, Xinjiang, September 8-11, 2007 (http://lsec.cc.ac.cn/̃ yyx/chinese/nlao2007-c.htm)

• International Conference on Numerical Optimization and Numerical Linear Algebra, L-hasa, Tibet, August 8-12, 2005 (http://lsec.cc.ac.cn/chinese/icmsec/new/xizang05.8.html)

• International Conference on Numerical Optimization and Numerical Linear Algebra,Guilin, Guangxi, May, 2003

• International Conference on Computational and Applied Mathematics, Beijing, August28-30, 2002 (http://lsec.cc.ac.cn/̃ yyx/conf02.html)

• International Conference on Numerical Optimization and Numerical Linear Algebra,Dunhuang, Gansu, May 17-20, 2001 (http://lsec.cc.ac.cn/̃ yyx/conf01.html)

• International Conference on Numerical Optimization and Numerical Linear Algebra,Nanjing, Jiangsu, September 27-30, 1999

• International Conference on Numerical Optimization and Numerical Linear Algebra,Qingdao, Shandong, October, 1997

Editorship and ResponsibilitySince 2018 General Secretary, The 24th International Symposium on Mathematical

Programming (ISMP2021)Since 2019.12 Director, Center for Optimization and Applications, AMSS, Chi-

nese Academy of Sciences.2016-2020 Vice President, Operations Research Society of China (ORSC)

Since 2016 Assistant President, AMSS, Chinese Academy of Sciences2014-2019 President, Mathematical Programming Subsociety of ORSC

Since 2014.7 Vice Editor-in-Chief, Mathematica Numerica SinicaSince 2013.7 Associate Editor, International Transactions in Operational Re-

searchSince 2013.1 Associate Editor, Journal of the Operations Research Society of

Chinasince 2013.1 Associate Editor, Statistics, Optimization & Information Com-

putingSince 2013.1 Associate Editor, Science China: MathematicsSince 2011.1 Associate Editor, Numerical Algebra, Control and Optimization

2011-2014 Associate Editor, Journal of Systems Science and Complexity2010-2018 Associate Editor, Operations Research and Management Science2010-2018 Associate Editor, Advances in Mathematics

Since 2009.12 Vice Director, Center for Optimization and Applications, AMSS,Chinese Academy of Sciences.

2009-2018 Associate Editor, Operations Research TransactionsSince 2008 Associate Editor, Asia-Pacific Journal of Operational Research2006-2014 Vice President, Mathematical Programming Subsociety of China

Major Grants• “Artificial Intelligence Methods for Mixed Integer Programming”, Major Projects of

Chinese Natural Science Foundation, 2020.1-2024.12, RMB4,620,000.• “Optimization Theory and Methods for Big Data Analysis”, Key Projects of Chinese

Natural Science Foundation, 2017.1-2021.12, RMB2,300,000.• “Statistical Learning of Unstructured Data: Mathematical Theory and Algorithms (Sub-

project: Optimization Methods for Unstructured Data)”, National Basic Research Pro-gram of China (973 Program), 2015.1-2019.12, RMB1,750,000.

• “Steady Operation Optimization Model and Algorithms for Gas Network”, PetroChinaPipeline Research & Development Center, 2015.11-2016.12, RMB480,000.

• “Network Optimization in Complicated Environment: Theory and Applications”, TheCAS Program for Cross & Cooperative Team of the Science & Technology Innovation,2013-2015, RMB1,000,000.

• “Middle Term Operation Optimization for Large-scale Stochastic New Energy, ChinaElectric Power Research Institute, 2013.8-2015.5, RMB 1,400,000.

• “SLP Algorithms and Application”, Beijing Shilin Computer Company, 2012.7-2013.7,RMB300,000.

• “Automatic Segmentation of White Matter Lesion Volumes and Applications”, ChineseNatural Science Foundation, 2012-2015.

• “Theory and Methods for Numerical Optimization”, The China National Funds for Dis-tinguished Young Scientists, 2012-2015, RMB1,400,000.

• “Optimization Theory and Applications”, The Special Foundation for State Major BasicResearch Program of China, 2009-2012.

• “Optimization Methods with Applications in Communications”, Knowledge InnovativeProgram of The Chinese Academy of Sciences, 2008-2011.

• “First order optimization method and applications”, Chinese Natural Science Founda-tion, 2006-2008, RMB240,000.

• “Studying Predictability Problems of El Nino and Torrential Rainfall via Nonlinear Op-timization”, Major Project of Chinese Natural Science Foundation, 2003-2006 (in coop-eration with Da-Qi Institute of CAS).

• “Algorithms and Theory for Large-Scale Optimization”, Chinese Natural Science Foun-dation, 2002-2004, RMB120,000.

• “Further Study on Nonlinear Conjugate Gradient Methods”, Chinese Natural ScienceFoundation for Youth, 1998-2001, RMB48,000.

• “Convergence Analysis of Quasi-Newton Methods”, Youth Creation Foundation of Chi-nese Academy of Sciences, 1998-2001, RMB50,000.

Teaching ExperiencesFebruary-June, 2008 Lecturing “Numerical Methods for Optimization” at the Graduate Uni-

versity of the Chinese Academy of Sciences (GUCAS).February-June, 2007 Lecturing “Practical Algorithms for Optimization” at GUCAS.February-June, 2001 Lecturing “Numerical Methods for Optimization” at GUCAS.

Ph.D. and Postdocs• Yue Zhang, from Univ. of Chinese Academy of Sciences, 2019-• Shengchao Wang, from Univ. of Chinese Academy of Sciences, 2019-• Cheng Zhao, from Sun Yat-sen Univ., 2019-• Qian Pei, from Sichuan Univ., 2019-• Shu Wang, from Beihang Univ., 2019- (postdoc)• Jinyu Dai, from Tsinghua Univ., 2019- (postdoc)• Zexian Liu, from Xidian Univ., 2019- (postdoc)• Shengjie Chen, from Xi’an Jiaotong Univ., 2018-• Ruijin Zhang, from Sichuan Univ., 2017-• Ting Zhang, from Tianjin Univ., 2017-2019 (postdoc)• Zhenyuan Ji, from Suzhou Univ., 2017-• Muming Yang, from Nankai Univ., 2016-• Na Huang, from Fujian Normal Univ., 2016-2018 (postdoc)• Zhe Jin, from China Univ. of Petroleum., 2015-2018 (master)

• Kai Fu, from Shandong Univ., 2015-• Liang Chen, from Nanjing Normal Univ., 2015-• Yakui Huang, from Xidian Univ., 2015.8-2017.5 (postdoc)• Weikun Chen, from Sun Yat-sen Univ., 2014-2019• Zhibao Li, from Hongkong Polytechnic Univ., 2014.5-2016.5 (postdoc)• Liaoyuan Zeng, from Hunan Univ., 2013-2018• Yanfang Zhang, from Hongkong Polytechnic Univ., 2012.10-2014.9 (postdoc)• Zhilong Dong, from Beihang Univ., 2012-2017• Dong Kang, from Wuhan Univ., 2012-2017• Chunfeng Cui, from Jilin Univ., 2011-2016• Tianxiang Liu, from Wuhan Univ., 2010-2015• Wenhui Zhang, from Shangdong Normal University, 2009-2014• Rui Diao, from Nankai Univ., 2009-2014• Xiaojuan Gu, from Beijing Univ., 2009.4-2011.4 (postdoc)• Bo Jiang, from China Univ. of Petroleum, 2008-2013• Yafeng Liu, from Xidian Univ., 2007-2012• Caixia Kou, from Beijing Normal Univ., 2006-2011• Minghou Chen, from Qufu Normal Univ., 2005-2010• Yunshan Fu, from Jijin Univ., 2005-2010• Zi Xu, from Hunan Nomral Univ., 2004-2009• Yiqing Hu, from Peking Univ., 2002-2007

Visitors Since 2014• Prof. Celso Ribiero, Universidade Fedral Fluminense, Brazil, from 28 June 19 to June

25, 2019.• Prof. Oleg Burdakov, Linkoping University, Sweden, from June 6 to June 26, 2018.• Prof. Florian Jarre, Heinrich-Heine-Universitat, Germany, from June 21 to July 20,

2017.• Prof. Deren Han, Nanjing Normal University, from June 8 to July 8, 2017.• Associate Prof. Lei Guo, Shanghai University of Finance Economics, from June 2 to

July 2, 2017.• Prof. Jiming Peng, University of Houston, USA, from May 15 to June 15, 2017.• Dr. Hui Zhang, National University of Defense Technology, from June 2 to July 2,

2017.• Prof. Deren Han, Nanjing Normal University, from June 23 to July 25, 2016.• Prof. Zhongwen Chen, Suchou University, from Oct. 22 to Nov. 22, 2015, ”A Penalty-

Free Method with Superlinear Convergence for Equality Constrained Optimization”.• Dr. Hui-Ju Chen, National Cheng Kung University, from July 16, 2014 to January

15, 2015, supported by The Taiwan Young Scientists Program of Chinese Academy ofSciences.

• Associate Prof. Liping Wang, Nanjing University of Aeronautics and Astronautics, fromJuly 23 to August 22, 2015.

• Prof. Nelson Maculan, Federal University of Rio de Janeiro, Brazil, from Dec. 6 to11, 2014, supported by the China-Brazil joint project funded by CAPES.

• Prof. Jinyun Yuan, Federal University of Parana, Curitiba, Brazil, from October 6,2014 to October 31, 2014, supported by the China-Brazil joint project funded by CAPES.

• Prof. Luis Roman Lucambio Perez, Instituto de Matematicae Estatistica, Univer-sidade Federal de Goias, Brazil, from October 1, 2014 to January 31, supported by theChina-Brazil joint project funded by CAPES.

• Associate Prof. Zhaosong Lv, Simon Fraser University, Canada, July 21-24, 2014,“Efficient Approaches for Two Big Data Matrix Optimization Problems”

• Associate Prof. Fengmin Xu, Xi’an Jiaotong University, July 21-24, 2014, “On Cardi-nality Constrained Optimization: Some Models and Algorithms”

• Assistant Prof. Shu Lu, University of North Carolina, Cape Hill, USA, July 18-19,2014, Title: “Confidence Regions and Intervals for Stochastic Variational Inequalities”

• Associate Prof. Jiming Peng, University of Houston, USA, July 3 to 6, 2014, “SomeOpportunities and Challenges in Optimization for Financial Engineering”

• Professor Christine Ann Shoemaker, Cornell University, USA, June 28 to July 12,2014 (giving a short course on surrogate-assistant global optimization from July 2 to 3)

• Associate Prof. Zhaosong Lv, Simon Fraser University, Canada, May 26 to July 6,2014.

• Professor Raimundo J. B. de Sampaio, Pontifical Catholic Univ. of Parana, BrazilNovember 15, 2013 to February 20, 2014, supported by the China-Brazil joint projectfunded by CAPES.

• Associate Prof. Orizon Pereira Ferreira, Universidade Federal de Goias, Brazil, fromNovember 5, 2013 to January 30, 2014, supported by the China-Brazil joint projectfunded by CAPES.

Books• Y.H. Dai and Y. Yuan (2000), Nonlinear Conjugate Gradient Methods, Shanghai Scien-

tific and Technical Publishers, Shanghai (in Chinese).

Special Issues• Special Topic on Optimization and OR 2020, CSAM Transaction on Applied Math-

ematics (CSAM), under organization (joint with Zhiquan (Tom) Luo and Zhijun Wu)• Special issue on Data-Driven Optimization 2020, International Transactions in Op-

erational Research, under organization (joint with Wei Bian, Chao Ding and XiaoWang)

• NACO Special Issue in Memory of WY Sun 2020, Numerical Algebra, Control andOptimization, under organization (joint with Naihua Xiu and Yiju Wang)

• Special Issue for MOA2018, Journal of Computational Mathematics, Vol. 37, No.6, 2020 (joint with Xiaojun Chen, Tamas Terlaky, Wotao Yin)

• Special Issue for MOA2016, Journal of Computational Mathematics, Vol. 36, No.3, 2018 (joint with Xiaojun Chen, Peter Richtarik, Yinyu Ye)

• Special Issue for ORSC2016, Operations Research Transactions, Vol. 21, No. 4,2017 (joint with Naihua Xiu, Guiying Yan, Xiaobo Zhao)

• Special Issue for ICIAM2015, Science China: Mathematics, Vol. 59, No. 8, 2016(joint with Zhaojun Bai, Weinan E, Chi-Wang Shu and Pingwen Zhang)

• Special Issue on Data-Driven Optimization Models and Algorithms, Journal of theOperations Research Society of China, Vol. 3, No. 4, 2015 (joint with Yanqin Baiand Naihua Xiu)

• Special Issue of The 2nd Sino-German Workshop on Optimization, Modeling, Methodsand Applications in Industry and Management, Pacific Journal of Optimization,Vol. 10, No. 1, 2014 (joint with Bingsheng He and Thorsten Koch).

• Special Issue of The 5th Sino-Japan Optimization Meeting, Asia-Pacific Journal ofOperational Research, Vol. 30, No. 3, 2013 (joint with Wenyun Sun and TetsuzoTanino)

• Special Issue on Conjugate Gradient and Quasi-Newton Methods for Nonlinear Opti-mization, Pacific Journal of Optimization, Vol. 2, No. 1, 2006 (joint with DonghuiLi).

Special Articles• Yu-Hong Dai, An Interview with Roger Fletcher, 2006• Yu-Hong Dai, Nonlinear Conjugate Gradient Methods, Wiley Encyclopedia of Op-

erations Research and Management Science, Published Online, Feb 2011, DOI: 10.1002/9780470400531.eorms0183

• Yu-Hong Dai, Xin Liu, Jiawang Nie and Zaiwen Wen, Preface (for Special issues ofOMS (35:2, 35:4) dedicated to Yaxiang Yuan’s 60 birthday), 2020

Papers1. Y.H. Dai and Y. Yuan (1996), Convergence Properties of the Fletcher-Reeves Method,

IMA Journal of Numerical Analysis 16 (2), pp. 155-164.2. Y.H. Dai and Y. Yuan (1996), Convergence Properties of the Conjugate Descent Method,

Advances in Mathematics 6, pp. 552-562.3. Y.H. Dai and Y. Yuan (1996), Convergence of the Fletcher-Reeves Method under A

Generalized Wolfe Search, Numer. Math. J. Chinese Univ. 2, pp. 142-148.4. Y.H. Dai and Y. Yuan (1998), Convergence Properties of the Beale-Powell Restart Al-

gorithm, Science in China (series A) 41 (11), pp. 1142-1150.5. Y.H. Dai and Y. Yuan (1998), Some Properties of A New Conjugate Gradient Method,

in: Y. Yuan ed., Advances in Nonlinear Programming (Kluwer, Boston), pp. 251-262.6. Y.H. Dai, J. Y. Han, G. H. Liu, D. F. Sun, H. X. Yin, and Y. Yuan (1999), Convergence

Properties of Nonlinear Conjugate Gradient Methods, SIAM Journal on Optimiza-tion 10 (2), pp. 345-358.

7. Y.H. Dai and Y. Yuan (1999), A Nonlinear Conjugate Gradient with A Strong GlobalConvergence Property, SIAM Journal on Optimization 10 (1), pp. 177-182.

8. Y.H. Dai and Y. Yuan (1999), Convergence Analyses of Three-term Conjugate GradientMethods, Mathematica Numericia Sinica 21 (3), pp. 355-362.

9. Y.H. Dai (1999), Further Insight Into the Convergence of the Fletcher-Reeves Method,Science in China (Series A) 42 (9), pp. 905-916.

10. Y.H. Dai and Y. Yuan (1999), Global Convergence of the Method of Shortest Residuals,Numerische Mathematik 83, pp. 581-598.

11. Y.H. Dai (2000), Some Properties of Memoryless Quasi-Newton Method, Journal onNumerical Methods and Computer Applications 1, pp. 28-32.

12. Y.H. Dai and Y. Yuan (2001), An Extended Class of Nonlinear Conjugate GradientMethods, In: D. Li eds. Proceedings of the 5th International Conference on Optimization:Techniques and Applications (December 2001, Hongkong), pp. 778-785.

13. Y.H. Dai and H. Zhang (2001), An Adaptive Two-Point Stepsize Gradient Algorithm,Numerical Algorithms, 27, pp. 377-385.

14. W.B. Liu and Y.H. Dai (2001), Minimization Algorithms Based on Supervisor andSearcher Cooperation, Journal of Optimization Theory and Applications, 111(2),pp. 359-379.

15. Y.H. Dai and Y. Yuan (2001) An Efficient Hybrid Conjugate Gradient Method for Un-constrained Optimization, Annals of Operations Research 103, pp. 33-47.

16. Y.H. Dai (2001), Convergence of Nonlinear Conjugate Gradient Methods, Journal ofComputational Mathematics 19 (5), pp. 539-548.

17. Y.H. Dai and Y. Yuan (2001), A Three-parameter Family of Nonlinear Conjugate Gra-dient Methods, Mathematics of Computation 70, pp. 1155-1167.

18. Y.H. Dai and L.Z. Liao (2001), New Conjugacy Condition and Its Resulting NonlinearConjugate Gradient Methods, Applied Mathematics and Optimization 43 (1), pp.87-101.

19. Y.H. Dai (2001), New Properties of A Nonlinear Conjugate Gradient Method, Nu-merische Mathematics 89 (1), pp. 83-98.

20. Y.H. Dai and Y. Yuan (2002), A Note on the Nonlinear Conjugate Gradient Method,Journal of Computational Mathematics, 20, pp. 575-582.

21. Y.H. Dai (2002), A Nonmonotone Conjugate Gradient Algorithm for Unconstrained Op-timization, Journal of Systems Science and Complexity, 15(2), 139-145.

22. Y.H. Dai, J.Y. Yuan, and Y. Yuan (2002), Modified Two-point Stepsize Gradient Methodsfor Unconstrained Optimization, Computational Optimization and Applications,22, 103-109.

23. Y.H. Dai (2002), Convergence Properties of the BFGS algorithm, SIAM Journal onOptimization, 13(3), pp. 693-701.

24. Y.H. Dai (2002), On the Nonmonotone Line Search, Journal of Optimization Theoryand Applications, 112 (2), pp. 315-330.

25. Y.H. Dai and L.Z. Liao (2002), R-Linear Convergence of the Barzilai and BorweinGradient Method, IMA Journal of Numerical Analysis, 22, 1-10.

26. Y.H. Dai (2003), Unified Convergence Analyses of Nonlinear Conjugate Gradient Meth-ods, in: Y.Yuan, ed. Numerical Linear Algebra and Optimization (Science Press, Bei-jing/NewYork, 2003) pp. 30-41.

27. W.B. Liu, Y.H. Dai and J. Lamb (2003), Novel supervisor-searcher cooperation algorithmsfor minimization problems with strong noise, Optimization Methods and Software,18, pp. 246-264.

28. Y.H. Dai and Y. Yuan (2003), Alternate Minimization Gradient Method, IMA Journalof Numerical Analysis, 23, pp. 377-393.

29. Y.H. Dai, J. M. Martínez, and J. Y. Yuan (2003), An Increasing-Angle Property ofthe Conjugate Gradient Method and the Implementation of Large-Scale MinimizationAlgorithms with Line Searches, Numerical Linear Algebra and Applications, 10:4,pp. 323-334.

30. Y.H. Dai and Y. Yuan (2003), A Class of Globally Convergent Conjugate GradientMethods, Sciences in China (series A) 46:2, pp. 251-261.

31. Y.H. Dai and Q. Ni (2003), Testing Different Conjugate Gradient Methods for Large-Scale Unconstrained Optimization, Journal of Computational Mathematics, 21:3,pp. 311-320.

32. Y.H. Dai and D.C. Xu (2003), A New Family of Trust Region Algorithms for Uncon-strained Optimization, Journal of Computational Mathematics 21:2, pp. 221-228.

33. Y.H. Dai (2003), Alternate Step Gradient Method, Optimization, 52:4-5, pp. 395-415.34. Y.H. Dai (2003), A Family of Hybrid Conjugate Gradient Methods for Unconstrained

Optimization, Mathematics of Computation, 72, pp. 1317-1328.

35. Y.H. Dai, L.Z. Liao and D. Li (2004), On Restart Procedures for the Conjugate GradientMethod, Numerical Algorithms, 35:2-4, pp. 249-260.

36. Y.H. Dai, J.Y. Yuan (2004), Study on Semi-Conjugate Gradient Methods for Non-Symmetric Linear Systems, International Journal for Numerical Methods in En-gineering, 60:8, pp. 1383-1399.

37. Y.H. Dai and R. Fletcher (2005), Projected Barzilai-Borwein Methods for Large-ScaleBox-Constrained Quadratic Programming, Numerische Mathematik, 100:1, pp. 21-47.

38. Y.H. Dai and R. Fletcher (2005), On the asymptotic behaviour of some new gradientmethods, Mathematical Programming, Series A, 13:3, pp. 541-559.

39. Y. H. Dai and Y. Yuan (2005), Analyses of Monotone Gradient Methods, Journal ofIndustry and Management Optimization, Vol. 1, No. 2, pp. 181-192.

40. Y.H. Dai, L.Z. Liao, D. Li (2005), An Analysis of Barzilai-Borwein Gradient Method forUnsymmetric Linear Equations, In: Optimization and control with applications (L. Qi,K. Teo and X. Yang, eds.), Springer, pp. 183-211.

41. Y.H.Dai, W.W. Hager, K.Schittkowski, H.C.Zhang (2006), The cyclic Barzilai-BorweinMethod for unconstrained optimization, IMA Journal of Numerical Analysis, 26:3,pp. 604-627.

42. B.Zhou, L.Gao and Y. H. Dai (2006), Monotone Projected Gradient Methods for Large-Scale Box-Constrained Quadratic Programming, Science in China,Series A, 36:5, pp.556-570.

43. B.Zhou, L. Gao and Y. H. Dai (2006), Gradient Methods with Adaptive Step-Sizes,Computational Optimization and Applications, 35:1, pp. 69-86.

44. Y.H. Dai and R. Fletcher (2006), New Algorithms for Singly Linearly ConstrainedQuadratic Programs Subject to Lower and Upper Bounds, Mathematical Program-ming, 16:3, pp. 403-421.

45. Y.H. Dai (2006), Fast Algorithms on Projection on an Ellipsoid, SIAM Journal onOptimization, 16:4, pp. 986-1006.

46. Y.H. Dai and X.Q. Yang (2006), A New Gradient Method with an Optimal StepsizeProperty, Computational Optimization and Applications, 33:1, pp. 73-88.

47. Y.Q.Hu and Y.H.Dai (2007), Inexact Barzilai-Borwein Method for Saddle Point Prob-lems, Numerical Linear Algebra with Applications, 14, pp. 299-317.

48. Z.Xu and Y.H.Dai (2008), A Stochastic Approximation Frame Algorithm with AdaptiveDirections, Numerical Mathematics-Theory Methods and Applications, 1:4, pp.460-474.

49. L.P.Wang and Y.H.Dai (2008), Left Conjugate Gradient Methods for Non-HermitianLinear Systems, Numerical Linear Algebra with Applications, 15, pp. 891-909.

50. Y. H. Dai and K. Schittkowski (2008), A Sequential Quadratic Programming Algorithmwith Non-Monotone Line Search, Pacific Journal of Optimization, 4£º2, pp. 335-351.

51. F. Li, Y. Fu, Y -H. Dai, C. Siminchisescu, J. Wang (2009), Kernel Learning by Un-constrained Optimization, Proceedings of the 12th International Conference on ArtificialIntelligence and Statistics (AISTATS), Clearwater Beach, Florida, USA, Volume 1 ofJMLR: WCP5, pp.328-335.

52. G. H. Yu, L. Q. Qi and Y. H. Dai (2009), On Nonmonotone Chambolle Gradient Pro-jection Algorithms for Total Variation Image Restoration, Journal of MathematicalImaging and Vision, 35:2, pp. 143-154.

53. Y.S. Fu and Y.H. Dai (2010), Improved Projected Gradient Algorithms for Singly LinearlyConstrained Quadratic Programs Subject to Lower and Upper Bounds, Asia-PacificJournal of Operational Research, 27:1, pp. 71-84.

54. M.H.Cheng and Y.H.Dai (2010), Sparse Two-Sided Rank-One Updates for NonlinearEquations, Sci. China Math, 53:11, pp. 2907-2915.

55. Y.F. Liu, Y. H. Dai and Z.Q. Luo (2010), On the Complexity of Optimal CoordinatedDownlink Beamforming, in: Proceedings of IEEE International Conference on Acoustics,Speech, and Signal Processing (ICASSP), Mar. 2010, pp. 3274-3277.

56. Y. H. Dai (2011), Convergence Analysis of Nonlinear Conjugate Gradient Methods, In:Optimization and Regularization for Computational Inverse Problems and Applications(Ed. by Y.Wang, A.G.Yagola and C.Yang), Springer, pp. 157-181.

57. Y. H. Dai(2010), Nonlinear Conjugate Gradient Methods, Wiley Encyclopedia ofOperations Research and Management Science, Published Online, Feb 2011, DOI:10.1002/ 9780470400531.eorms0183.

58. Y.H.Dai (2011), Convergence of Conjugate Gradient Methods with Constant Stepsizes,Optimization Methods and Software, 26:6, pp.895-909.

59. Y. F. Liu, Y. H. Dai and Z. Q. Luo (2011), Coordinated Beamforming for MISO Interef-erence Channel: Complexity Analysis and Efficient Algorithms, IEEE Transactionson Signal Processing, 59:3, pp.1142-1157.

60. Y.-F. Liu, Y. H. Dai, and Z.-Q. Luo (2011), Max-min fairness linear transceiver designfor a multi-user MIMO interference channel, in: Proc. IEEE International Conferenceon Communications, Jun. 2011, pp. 1-5.

61. Y.-F. Liu, Y. H. Dai, and Z.-Q. Luo (2011), On the complexity of leakage interferenceminimization for interference alignment, in: Proc. IEEE 12th International Workshopon Signal Processing Advances in Wireless Communications, Jun. 2011, pp. 471-475.

62. Y. H. Dai and N. Yamashita (2011), Convergence analysis of sparse quasi-Newton up-dates with positive definite matrix completion for two-dimensional functions, NumericalAlgebra, Control and Optimization, 1:1, pp. 61-69.

63. M. Cheng, Y. H. Dai (2012), Adaptive Nonmonotone Spectral Residual Method for Large-scale Nonlinear Systems, Pacific Journal of Optimization, 8:1, pp. 15-25.

64. Y. H. Dai (2012), A General Convergence Result for the BFGS Method, ComputationalMethods for Applied Inverse Problems (Ed. by Y. F. Wang, A. G. Yagola and C. C.Yang), De Gruyter and Higher Education Press, DOI: 10.1515/9783110259056, pp. 241-248.

65. Z. Xu and Y. H. Dai (2012), New Stochastic Approximation Algorithms with AdaptiveStep Sizes, Optimization Letters, 6, pp. 1831-1846.

66. Y. H. Dai (2013), A Perfect Example for the BFGS Method, Mathematical Program-ming, Ser. A, 138:1-2, pp. 501-530.

67. Y. H. Dai and C. X. Kou (2013), A Nonlinear Conjugate Gradient Algorithm with An Op-timal Property and An Improved Wolfe Line Search, SIAM Journal on Optimization,23:1, pp. 296-320.

68. Y. N. Chen, Y. H. Dai, D. R. Han and W. Y. Sun (2013), Positive Semidefinite General-ized Diffusion Tensor Imaging via Quadratic Semidefinite Programming, SIAM Journalon Imaging Sciences, 6:3, pp. 1531-1552.

69. Y. F. Liu, Y. H. Dai, Z. Q. Luo (2013), Max-Min Fairness Linear Transceiver Design for aMulti-User MIMO Interference Channel, IEEE Transactions on Signal Processing,61:9, pp. 2413-2423.

70. Y. F. Liu, Y. H. Dai, Z. Q. Luo (2013), Joint Power and Admission Control via LinearProgramming Deflation, IEEE Transactions on Signal Processing, 61:6, pp. 1327-1338.

71. Y. F. Liu, M. Hong, Y. H. Dai (2013), Max-Min Fairness Linear Transceiver DesignProblem for a Multi-User SIMO Interference Channel Is Polynomial Time Solvable,IEEE Signal Processing Letters, 20:1, pp. 27-30.

72. Y. F. Liu and Y. H. Dai (2013), Joint Power and Admission Control via P -Norm Nini-mization Deflation, in: Proc. IEEE International Conference on Acoustics, Speech, andSignal Processing (ICASSP), pp. 4789-4793.

73. Y. H. Dai (2013), A New Analysis on the Barzilai-Borwein Gradient Method, Journalof Operations Research Society of China, 1:2, pp. 187-198.

74. B. Jiang, Y. H. Dai (2013), Feasible Barzilai-Borwein-Like Methods for Extreme Symmet-ric Eigenvalue Problems, Optimization Methods and Software, 28:4, pp. 756-784.

75. Y. H. Dai and N. Yamashita (2014), Analysis of Sparse Quasi-Newton Updates withPositive Definite Matrix Completion, Journal of the Operations Research Societyof China, 2:1, pp. 39-56.

76. Y. F. Liu and Y. H. Dai (2014), On the Complexity of Joint Subcarrier and Power Allo-cation for Multi-User OFDMA Systems, IEEE Transactions on Signal Processing,62:3, pp. 583-596.

77. C. F. Cui, Y. H. Dai, J. W. Nie (2014), All Real Eigenvalues of Symmetric Tensors,Accepted by SIAM Journal on Matrix Analysis and Applications.

78. C. X. Kou and Y. H. Dai (2014), A Modified Self-Scaling Memoryless Broyden-Fletcher-Goldfarb-Shanno Method for Unconstrained Optimization, Journal of OptimizationTheory and Applications, DOI 10.1007/s10957-014-0528-4

79. H. Gao, Y. H. Dai and X. J. Tong (2014), Barzilai-Borwein-Like Methods for The Ex-treme Eigenvalue Problem, Journal of Industrial and Management Optimization,DOI 10.3934/jimo.2015.11.999

80. C. L. Hao, C. F. Cui and Y. H. Dai (2014), A Sequential Subspace Projection Method forExtreme Z-Eigenvalues of Supersymmetric Tensors, Numerical Linear Algebra andApplications, DOI: 10.1002/nla.1949

81. B. Jiang, C. Cui and Y. H. Dai (2014), Unconstrained Optimization Models for Com-puting Several Extreme Eigenpairs of Real Symmetric Matrices, Pacific Journal ofOptimization, 10:1, pp. 55-71.

82. Y. H. Dai and X. W. Liu (2014), Advances in linear and nonlinear programming, Op-erations Research Transactions, 18:1, pp. 69-92 (in Chinese).

83. Y. H. Dai, M. Al-Baali and X. Yang (2015), A positive Barzilai-Borwein-like stepsizeand an extension for symmetric linear systems, In: M. Al-Baali, L. Grandinetti and A.Purnama eds., Vol. 134 of the series Springer Proceedings in Mathematics & Statistics:Numerical Analysis and Optimization, pp. 59-75.

84. B. Jiang and Y. H. Dai (2015), A Framework of Constraint Preserving Update Schemesfor Optimization on Stiefel Manifold, Mathematical Programming, Ser. A, 153:2,pp. 535-575.

85. Y.F. Liu, S. Ma, Y.H. Dai and S. Zhang (2016), A Smoothing SQP Framework for AClass of Composite Lq Minimization over Polyhedron, Mathematical Programming,Ser. A, 158, pp. 467-500.

86. Y.N. Chen, Y.H. Dai and D.R. Han (2016), Fiber Orientation Distribution EstimationUsing a Peaceman-Rachford Splitting Method, SIAM J. Imaging Sciences, 9:2, pp.573-604.

87. Y.H. Dai and C.X. Kou (2016), A Barzilai-Borwein Conjugate Gradient Method, ScienceChina Mathematics, 59:8, pp. 1511-1524.

88. C. Tan, S. Ma, Y.H. Dai and Y. Qian (2016), Barzilai-Borwein Step Size for Stochas-tic Gradient Descent, Accepted by The 30th Conference on Neural InformationProcessing Systems (NIPS), Barcelona, Spain.

89. Z.W. Chen and Y.H. Dai (2016), A Line Search Exact Penalty Method Without Bi-objective Strategy for Nonlinear Constrained Optimization, Journal of Computationaland Applied Mathematics, 300, pp. 245-258.

90. F. Xu, M. Sun and Y.H. Dai (2016), An Adaptive Lagrangian Algorithm for OptimalPortofolio Deleveraging with Cross-impact, Journal of Systems Science and Com-plexity.

91. Z.B. Li and Y.H. Dai (2016), Optimal Beamforming Design in the Reverberant Environ-ment, Scientia Sinica Mathematica, 46:6, pp. 877-892.

92. M. Liu, C. Cui, X. Tong and Y.H. Dai (2016), Algorithms, Softwares and Recent De-velopments of Mixed Integer Nonlinear Programming, Scientia Sinica Mathematica,46:1, pp. 1-20 (in Chinese).

93. M. Liu, X. Tong and Y.H. Dai (2016), Algorithms and Recent Developments of Pack-ing Problems (in Chinese), Mathematica Numerica Sinica, 38:3, pp. 257-280 (inChinese)

94. G.X. Li, C.K. Chen, Z. Wan and Y.H. Dai (2016), Integer Programming Model for Trans-port Aircraft Fleet Cargo Loading, Journal on Numerical Methods and ComputerApplications, 37:3, pp. 233-244 (in Chinese).

95. Y. H. Dai, D. Han, X. Yuan and W. Zhang (2016), A sequential updating scheme of La-grange multiplier for separable convex programming, Mathematics of Computation,http://dx.doi.org/10.1090/mcom/3104.

96. Y. N. Chen, Y. H. Dai and D. R. Han (2016), Fiber orientation distribution estimationusing a Peaceman-Rachford splitting method, SIAM J. Imaging Sciences, 9:2, pp.573-604.

97. Y. F. Liu, S. Ma, Y. H. Dai and S. Zhang (2016), A smoothing SQP framework for aclass of composite Lq minimization over polyhedron, Mathematical Programming,Ser. A, 158, pp. 467-500.

98. Z. W. Chen and Y. H. Dai (2016), A line search exact penalty method without bi-objectivestrategy for nonlinear constrained optimization, Journal of Computational and Ap-plied Mathematics, 300, pp. 245-248.

99. Z. B. Li and Y. H. Dai (2016), Optimal beamforming design in the reverberant environ-ment, Science Sinica Mathematica, 46:6, pp. 877-892.

100. Y.H. Dai, D. Han, X. Yuan and W. Zhang (2017), A Sequential Updating Scheme of La-grange Multiplier for Separable Convex Programming, Mathematics of Computation,86:303, pp. 315-343.

101. R. Diao, Y.F. Liu and Y.H. Dai (2017), A New Fully Polynomial Time ApproximationScheme for the Interval Subset Sum Problem, Journal of Global Optimization, 68:4,pp. 749-775.

102. F.M. Xu, Y.H. Dai, Z.H. Zhao and Z.B. Xu (2017), Efficient Projected Gradient Methodsfor A Class of L0 Constrained Optimization Problems, Accepted by Science China:Mathematics.

103. Y.K. Huang, B. Li, Y. Kang, Y.H. Dai and J.J. Liu (2017), A Mixed Integer Modeland An Algorithm for Steady-State Gas Network Optimization, Operations ResearchTransactions, 21:2, pp. 13-23 (in Chinese).

104. Y.H. Dai, R. Diao and K. Fu (2018), Complexity Analysis and Algorithm Design ofPooling Problem, Journal of the Operations Research Society of China, 6:2�pp.249-266.

105. W.Y. Cheng and Y.H. Dai (2018), Gradient-based Method with Active Set Strategy forℓ1 optimization, Mathematics of Computation, 87, pp. 1283-1305.

106. C. Kou, Z.W. Chen and Y.H. Dai (2018), An Augmented Lagrangian Trust Region Methodwith A Bi-Objective Strategy, Journal of Computational Mathematics, 36:3, pp.331-350.

107. F. Xu, M. Wang, Y.H. Dai and D. Xu (2018), A Sparse Enhanced Indexation Modelwith Chance and Cardinality Constraints, Journal of Global Optimization, 70:1, pp.5-25.

108. Z. Li, K. Yiu and Y.H. Dai (2018), On Sparse Beamformer Design with Reverberation,Applied Mathematical Modelling, 58, pp. 98-110.

109. S. Chen, Y.H. Dai and F. Xu (2018), On the Study of Sparse Linear Programming,Mathematica Numerica Sinica, 40:4, pp. 339-353 (in Chinese).

110. W.K. Chen, L. Chen, M.M. Yang, Y.H. Dai (2018), Generalized Coefficient StrengtheningCuts for Mixed Integer Programming, Journal of Global Optimization, 70, pp. 289-306.

111. C. Kou, Z. Chen and Y.H. Dai, An Augmented Lagrangian Trust Region Method with ABi-Objective Strategy, Journal of Computational Mathematics, 36:3, pp. 331-350.

112. F. Xu, Y. H. Dai, Z. Zhao, Z. B. Xu (2019), Efficient Projected Gradient Methods forCardinality Constrained Optimization, Science China: Mathematics, 62:2, pp. 245-268.

113. L. Zeng and Y.H. Dai, Convergence Rate of Gradient Descent Method for Multi-ObjectiveOptimization, Journal of Computational Mathematics, 37:5, pp. 689-703.

114. O. Burdakov, Y.H. Dai and N. Huang (2019), Stabilized Barzilai-Borwein Method, Jour-nal of Computational Mathematics, 37:6, pp. 916-936.

115. Z. Wang, Y.H. Dai and F. Xu (2019), A Robust Interior Point Method for Computingthe Analytic Center of An Ill-Conditioned Polytope with Errors, Journal of Compu-tational Mathematics, 37:6, pp. 843-865.

116. L. Chen, Y.H. Dai and Z. Wei (2019), An Outer Approximation Method for A Class ofMinimax Convex MINLP Problems, Journal of Nonlinear and Convex Analysis,20:3, pp. 379-393.

117. Z. Li, Y.H. Dai and H. Gao (2019), Alternating Projection Method for A Class of TensorEquations, Journal of Computational and Applied Mathematics, 346, pp. 490-504.

118. Y.H. Dai, X.W. Liu and J. Sun (2020), A Primal-Dual Interior-Point Method Capableof Rapidly Detecting Infeasibility for Nonlinear Programs, Journal of Industrial andManagement Optimization, 16:2, pp. 1009-1035.

119. X.W. Liu and Y.H. Dai (2020), A Globally Convergent Primal-Dual Interior-Point Re-laxation Method for Nonlinear Programs, Mathematics of Computation, 89:323, pp.1301-1329.

120. Z. Liu, H. Liu and Y.H. Dai (2020), An Improved Dai–Kou Conjugate Gradient Algorithmfor Unconstrained Optimization, Computational Optimization and Applications,75, pp. 145-167.

121. Y.H. Dai, Y. Huang, X.W. Liu, A Family of Spectral Gradient Methods for Optimization,accepted by Computational Optimization and Applications.https://doi.org/10.1007/s10589-019-00107-8

122. Z. Chen, Y.H. Dai and J. Liu, A Penalty-Free Method with Superlinear Convergencefor Equality Constrained Optimization, accepted by Numerical Linear Algebra withApplications.https://doi.org/10.1007/s10589-019-00117-6

123. An Exact Penalty Method for Semidefinite-Box Constrained Low-Rank Matrix Opti-mization Problems (X. Chen, Y.-H. Dai and T. Liu), accepted by IMA Journal ofNumerical Analysis.

124. N. Huang, Y.H. Dai, Q. Hu, Uzawa Methods for A class of Block Three-by-Three Saddle-Point Problems, accepted by Numerical Linear Algebra with Applications.

https://doi.org/10.1002/nla.2265125. M. Yang, Y. Huang, Y.H. Dai and B. Li, An Efficient Global Optimization Algorithm for

Heated Oil Pipeline Problems, accepted by Industrial and Engineering ChemistryResearch. DOI: 10.1021/acs.iecr.0c00039

126. Y. Zhang, Y.H. Dai, W. Han, Z. Li, Smoothing Quadratic Regularization Method forHemivariational Inequalities, accepted by Optimization.https://doi.org/10.1080/02331934.2020.1712393

127. Y. Huang, Y.H. Dai, X.W. Liu and H. Zhang (2020), Gradient Methods Exploiting Spec-tral Properties, accepted by Optimization Methods and Software.https://doi.org/10.1080/10556788.2020.1727476

128. Y. H. Dai, F. Jarre and F. Lieder (2020), On the Existence of Affine Invariant DescentDirections, Optimization Methods and Software.https://doi.org/10.1080/10556788.2020.1740221.

129. W. Chen and Y. H. Dai (2020), On the Complexity of Sequentially Lifting Cover Inequal-ities for the Knapsack Polytope, Science China Mathematics.https://doi.org/10.1007/s11425-019-9538-1

130. K. Liao, Y. Hu, X. Hou, L. Wu, J. Wang, Y. Zhang, Y.H. Dai and Z. Yang (2020),The Quantitative Analysis of Causality between Population Migration and the Numberof Newly Confirmed Cases, accepted by Mathematical Modeling and Its Applications.

131. Z. Ding, Y. Liu, J. Kong, H. Zhang, Y. Zhang, Y.H. Dai and Z. Yang (2020), A ProbabilityModel for Estimating the Expected Number of the Newly Infected and Predicting the Trendof the Diagnosed , Operations Research Transactions, 24:1, pp. 1-12.

132. Y. Hu, J. Kong, L. Yang, X. Wang, Y. Zhang, Y.H. Dai and Z. Yang (2020), A DynamicGrowth Rate Model and Its Application in Global Epidemic Analysis, Acta Mathemat-icae Applications Sinica, 43:1, pp. 1-15.

133. Y. Hu, Y. Liu, L. Wu, J. Wang, J. Dong, Y. Zhang, Y.H. Dai and Z. Yang (2020), A Dy-namic Transmission Rate Model and Its Application in Epidemic Analysis, OperationsResearch Transactions.

134. W. Peng, Y.H. Dai, H. Zhang and L. Cheng, Training GANs with Centripetal Accelera-tion, accepted by Optimization Methods and Software.https://doi.org/10.1080/10556788.2020.1754414

135. H. Zhang, L. Guo, Y.H. Dai and W. Peng, Proximal-Like Incremental Aggregated Gra-dient Method with Linear Convergence under Bregman Distance Growth Conditions,accepted by Mathematics of Operations Research.