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<nowiki>[</nowiki>[MainPage|Back to main page] <nowiki>]</nowiki> ===Manuscripts=== * Yu-Ren Liu, Yi-Qi Hu, Hong Qian, __Yang Yu__, and Chao Qian. ''ZOOpt: Toolbox for derivative-free optimization''. [^https://arxiv.org/abs/1801.00329|arXiv:1801.00329], 2018. ===Book=== * Zhi-Hua Zhou, __Yang Yu__ and Chao Qian. Evolutionary Learning: Advances in Theories and Algorithms, Berlin: Springer, 2019. (ISBN 978-981-13-5955-2) ([^https://www.springer.com/cn/book/9789811359552|Springer Link]) ===Book Chapter=== * Zhi-Hua Zhou and __Yang Yu__. ''The AdaBoost algorithm''. In: X. Wu and V. Kumar eds. '''The Top Ten Algorithms in Data Mining''', Boca Raton, FL: Chapman & Hall, 2009. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/top10chapter.pdf|PDF]) ===Conference Papers=== * Jianhao Wang, Zhizhou Ren, Terry Liu, __Yang Yu__, Chongjie Zhang. ''QPLEX: Duplex dueling multi-agent Q-Learning''. In: '''Proceedings of the 9th International Conference on Learning Representations (ICLR'21)''', Virtual Conference, 2021. * Tian Xu, Ziniu Li, __Yang Yu__. ''Error bounds of imitating policies and environments''. In: '''Advances in Neural Information Processing Systems 33 (NeurIPS'20)''', Virtual Conference, 2020. ([{UP}papers/nips2020_missimulator.pdf|PDF]) * Shengyi Jiang, Jing-Cheng Pang, __Yang Yu__. ''Offline imitation learning with a misspecified simulator''. In: '''Advances in Neural Information Processing Systems 33 (NeurIPS'20)''', Virtual Conference, 2020. ([{UP}papers/nips2020_imitating.pdf|PDF]) * Yi-Qi Hu, Zelin Liu, Hua Yang, __Yang Yu__, and Yunfeng Liu. ''Derivative-free optimization with adaptive experience for efficient hyper-parameter tuning''. In: '''Proceedings of the 24th European Conference on Artificial Intelligence (ECAI'20)''', Santiago de Compostela, Spain, 2020. ([{UP}papers/ECAI20-AdaExp.pdf|PDF]) * Chao Bian, Chao Feng, Chao Qian, and __Yang Yu__. ''An efficient evolutionary algorithm for subset selection with general cost constraints''. In: '''Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI'20)''', New York, NY, 2020. ([{UP}papers/aaai20-eamc-final.pdf|PDF]) * Wang-Zhou Dai, Qiuling Xu, __Yang Yu__, and Z.-H. Zhou. ''Bridging machine learning and logical reasoning by abductive learning''. In: '''Advances in Neural Information Processing Systems 32 (NeurIPS'19)''', Vancouver, Canada, 2019. ([{UP}papers/neurips19abl.pdf|PDF]) ([^https://github.com/AbductiveLearning/ABL-HED|Code]) * Yu-Ren Liu, Yi-Qi Hu, Hong Qian, __Yang Yu__. ''Asynchronous Classification-Based Optimization''. In: '''Proceedings of the 1st International Conference on Distributed Artificial Intelligence (DAI'19)''', Beijing, China, 2019. ([{UP}papers/dai-19.pdf|PDF]) * Xiong-Hui Chen, __Yang Yu__. ''Reinforcement Learning with Derivative-Free Exploration''. In: '''Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS'19)''', Montreal, Canada, 2019, pp.1880-1882. ([{UP}papers/ijcai19-ERUCB.pdf|PDF]) * Yi-Qi Hu, __Yang Yu__ and Jun-Da Liao. ''Cascaded algorithm-selection and hyper-parameter optimization with extreme-region upper confidence bound bandit.'' In: '''Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19)''', Macao, China, 2019. ([{UP}papers/ijcai19-ERUCB.pdf|PDF]) * Wen-Ji Zhou, __Yang Yu__, Yingfeng Chen, Kai Guan, Tangjie Lv, Changjie Fan and Zhi-Hua Zhou. ''Reinforcement learning experience reuse with policy residual representation''. In: '''Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI'19)''', Macao, China, 2019. ([{UP}papers/ijcai19-PRR.pdf|PDF]) * Wenjie Shang, __Yang Yu__, Qingyang Li, Zhiwei Qin, Yiping Meng and Jieping Ye. ''Environment reconstruction with hidden confounders for reinforcement learning based recommendation''. In: '''Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'19)''' (Research Track), Anchorage, AL, 2019. ([{UP}papers/kdd19-confounder.pdf|PDF]) * Jing-Cheng Shi, __Yang Yu__, Qing Da, Shi-Yong Chen, and An-Xiang Zeng. ''Virtual-Taobao: Virtualizing real-world online retail environment for reinforcement learning''. In: '''Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI’19)''', Honolulu, HI, 2019. ([{UP}papers/aaai2019-virtualtaobao.pdf|PDF]) * Yi-Qi Hu, __Yang Yu__, Wei-Wei Tu, Qiang Yang, Yuqiang Chen, and Wenyuan Dai. ''Multi-fidelity automatic hyper-parameter tuning via transfer series expansion''. In: '''Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI’19)''', Honolulu, HI, 2019. ([{UP}papers/aaai19_huyq.pdf|PDF]) * Zhen-Jia Pang, Ruo-Ze Liu, Zhou-Yu Meng, Yi Zhang, __Yang Yu__, and Tong Lu. ''On reinforcement learning for full-length game of StarCraft''. In: '''Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI’19)''', Honolulu, HI, 2019. ([{UP}papers/aaai2019-sc.pdf|PDF]) * Ji Feng, __Yang Yu__, Zhi-Hua Zhou. ''Multi-layered gradient boosting decision trees''. In: '''Advances in Neural Information Processing Systems 31 (NIPS'18)''', Montreal, Canada, 2018. [^https://arxiv.org/abs/1806.00007|arXiv:1806.00007]. * __Yang Yu__. ''Towards sample efficient reinforcement learning.'' In: '''Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18) (Early Career)''', Stockholm, Sweden, 2018, pp.5739-5743. ([{UP}papers/ijcai18-EfficientRL.pdf|PDF]) * Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales, Wei-Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon, and Michele Sebag. ''Towards AutoML in the presence of drift: First results. '' In: '''ICML 2018 Workshop on AutoML''', Stockholm, Sweden, 2018. * Shi-Yong Chen, __Yang Yu__, Qing Da, Jun Tan, Hai-Kuan Huang and Hai-Hong Tang. ''Stabilizing reinforcement learning in dynamic environment with application to online recommendation''. In: '''Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18)''' (Research Track), London, UK, 2018. ([{UP}papers/kdd18-RobustDQN.pdf|PDF]) * Yujing Hu, Qing Da, Anxiang Zeng, __Yang Yu__ and Yinghui Xu. ''Reinforcement learning to rank in e-commerce search engine: Formalization, analysis, and application''. In: '''Proceedings of the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'18)''' (Applied Track), London, UK, 2018. ([{UP}papers/kdd18-rec.pdf|PDF]) * Chao Qian, Chao Bian, __Yang Yu__, Ke Tang, and Xin Yao. ''Analysis of noisy evolutionary optimization when sampling fails''. In: '''Proceedings of the 20th ACM Conference on Genetic and Evolutionary Computation (GECCO'18)''', Kyoto, Japan, 2018. ([{UP}papers/gecco18-sampling.pdf|PDF]) * __Yang Yu__, Wen-Ji Zhou. ''Mixture of GANs for clustering.'' In: '''Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18)''', Stockholm, Sweden, 2018, pp.3047-3053. ([{UP}papers/ijcai18-GANMM.pdf|PDF]) * Chao Zhang, __Yang Yu__, Zhi-Hua Zhou. ''Learning environmental calibration actions for policy self-evolution''. In: '''Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18)''', Stockholm, Sweden, 2018, pp.3061-3067. ([{UP}papers/ijcai18-POSEC.pdf|PDF]) * Yi-Qi Hu, __Yang Yu__, Zhi-Hua Zhou. ''Experienced optimization with reusable directional model for hyper-parameter search''. In: '''Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18)''', Stockholm, Sweden, 2018, pp.2276-2282. ([{UP}papers/ijcai18-ExpOpt.pdf|PDF]) * Chao Qian, __Yang Yu__, Ke Tang. ''Approximation guarantees of stochastic greedy algorithms for subset selection.'' In: '''Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI'18)''', Stockholm, Sweden, 2018, pp.1478-1484. ([{UP}papers/ijcai18-StochasticGreedy-ChaoQian.pdf|PDF]) * Hong Wang, Hong Qian, and __Yang Yu__. ''Noisy derivative-free optimization with value suppression''. In: '''Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI’18)''', New Orleans, LA, 2018. ([{UP}papers/aaai18-supress.pdf|PDF]) * Chao Qian, Jing-Cheng Shi, __Yang Yu__, Ke Tang, and Zhi-Hua Zhou. ''Subset selection under noise''. In: '''Advances in Neural Information Processing Systems 30 (NIPS'17)''', Long Beach, CA, 2017. ([{UP}papers/nips17-ponss.pdf|PDF with Appendix]) * Jing-Cheng Shi, Chao Qian, and __Yang Yu__. ''Evolutionary multi-objective optimization made faster by sequential decomposition''. In: '''Proceedings of the 2017 IEEE Congress on Evolutionary Computation (CEC'17)''', San Sebastian, Spain, 2017. ([{UP}papers/cec17-moea-sd.pdf|PDF]) * __Yang Yu__, Wei-Yang Qu, Nan Li, and Zimin Guo. ''Open category classification by adversarial sample generation''. In: '''Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)''', Melbourne, Australia, 2017, pp.3357-3363. ([{UP}papers/ijcai17-ASG-longer.pdf|PDF])([^https://github.com/eyounx/ASG|Code]) * Wen-Ji Zhou, __Yang Yu__, and Min-Ling Zhang. ''Binary linear compression for multi-label classification''. In: '''Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)''', Melbourne, Australia, 2017, pp.3546-3552. ([{UP}papers/ijcai17-bilc.pdf|PDF]) * Jing-Wen Yang, __Yang Yu__, and Xiao-Peng Zhang. ''Life-stage modeling by customer-manifold embedding''. In: '''Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)''', Melbourne, Australia, 2017, pp.3259-3265. ([{UP}papers/ijcai17-UserManifold.pdf|PDF]) * Chao Qian, Jing-Cheng Shi, __Yang Yu__, Ke Tang and Zhi-Hua Zhou. ''Optimizing ratio of monotone set functions''. In: '''Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)''', Melbourne, Australia, 2017, pp.2606-2612. ([{UP}papers/ijcai17-porm.pdf|PDF]) ([^http://lamda.nju.edu.cn/code_PORM.ashx|Code]) * Chao Qian, Jing-Cheng Shi, __Yang Yu__, and Ke Tang. ''On subset selection with general cost constraints''. In: '''Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)''', Melbourne, Australia, 2017, pp.2613-2619. ([{UP}papers/ijcai17-pomc.pdf|PDF]) ([^http://lamda.nju.edu.cn/code_POMC.ashx|Code]) * Jianbing Zhang, Yixin Sun, Shu-Jian Huang, Cam-Tu Nguyen, Xiaoliang Wang, Xin-Yu Dai, Jiajun Chen, and __Yang Yu__. ''AGRA: An analysis-generation-ranking framework for automatic abbreviation from paper titles''. In: '''Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI'17)''', Melbourne, Australia, 2017, pp.4221-4227. ([{UP}papers/ijcai17-abbr.pdf|PDF]) ([^http://nlp.nju.edu.cn/demo/abbreviation.html|online demo]) * Hong Qian and __Yang Yu__. ''Solving high-dimensional multi-objective optimization problems with low effective dimensions''. In: '''Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17)''', San Francisco, CA, 2017, pp.875-881. ([{UP}papers/aaai17-remo-with-appendix.pdf|PDF with Appendix]) * Yi-Qi Hu, Hong Qian, and __Yang Yu__. ''Sequential classification-based optimization for direct policy search''. In: '''Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI’17)''', San Francisco, CA, 2017, pp.2029-2035. ([{UP}papers/aaai17-sracos-with-appendix.pdf|PDF with Appendix]) ([code_racos|Code]) * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''A lower bound analysis of population-based evolutionary algorithms for pseudo-Boolean functions''. In: '''Proceedings of the 17th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'16)''', Yangzhou, China, 2016, pp.457-467. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/ideal16.pdf|PDF]) <font color="blue">(This paper won a Best Paper Award of IDEAL'16)</font> * Xin Li, Yongjuan Liang, Hong Qian, Yi-Qi Hu, Lei Bu, __Yang Yu__, Xin Chen, and Xuandong Li. ''Symbolic execution of complex program driven by machine learning based constraint solving''. In: '''Proceedings of the 31th IEEE/ACM International Conference on Automated Software Engineering (ASE'16)''', Singapore, 2016, pp.554-559. ([^http://dl.acm.org/ft_gateway.cfm?id=2970364&type=pdf|PDF]) * Han Wang and __Yang Yu__. ''Exploring multi-action relationship in reinforcement learning''. In: '''Proceedings of the 14th Pacific Rim International Conference on Artificial Intelligence (PRICAI'16)''', Phuket, Thailand, 2016, pp.574–587. ([{UP}papers/pricai16-multiaction.pdf|PDF]) * Hong Qian, Yi-Qi Hu and __Yang Yu__. ''Derivative-free optimization of high-dimensional non-convex functions by sequential random embeddings''. In: '''Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16)''', New York, NY, 2016, pp.1946-1952. ([{UP}papers/ijcai16-sre.pdf|PDF]) ([^https://github.com/eyounx/SRE|Code]) * Chao Qian, Jing-Cheng Shi, __Yang Yu__, Ke Tang, and Zhi-Hua Zhou. ''Parallel Pareto optimization for subset selection''. In: '''Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI'16)''', New York, NY, 2016, pp.1939-1945. ([{UP}papers/ijcai16-pposs.pdf|PDF]) * Hong Qian and __Yang Yu__. ''On sampling-and-classification optimization in discrete domains''. In: '''Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC'16)''', Vancouver, Canada, 2016, pp.4374-4381. ([{UP}papers/cec16-sac-ea.pdf|PDF]) * __Yang Yu__, Peng-Fei Hou, Qing Da, and Yu Qian. ''Boosting nonparametric policies''. In: '''Proceedings of the 2016 International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'16)''', Singapore, 2016, pp.477-484. ([{UP}papers/aamas16_policyboost.pdf|PDF]) ([code_funcpolicy|Code]) * __Yang Yu__, Hong Qian, and Yi-Qi Hu. ''Derivative-free optimization via classification''. In: '''Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16)''', Phoenix, AZ, 2016, pp.2286-2292. ([{UP}papers/aaai16-racos.pdf|PDF]) ([{UP}papers/aaai16-racos-appendix.pdf|Appendix]) ([code_racos|Code]) * Hong Qian, __Yang Yu__. ''Scaling simultaneous optimistic optimization for high-dimensional non-convex functions with low effective dimensions''. In: '''Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI'16)''', Phoenix, AZ, 2016, pp.2000-2006. ([{UP}papers/aaai16-resoo.pdf|PDF]) * Chao Qian, __Yang Yu__ and Zhi-Hua Zhou. ''Subset selection by Pareto optimization''. In: '''Advances in Neural Information Processing Systems 28 (NIPS'15)''' , Montreal, Canada, 2015. ([{UP}papers/nips15-poss.pdf|PDF]) ([^http://lamda.nju.edu.cn/code_POSS.ashx|code]) * Chao Qian, __Yang Yu__ and Zhi-Hua Zhou. ''On constrained Boolean Pareto optimization''. In: '''Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI'15)''', Buenos Aires, Argentina, 2015, pp.389-395. ([{UP}papers/ijcai15-constrained.pdf|PDF]) * __Yang Yu__, Chao Qian. ''Running time analysis: Convergence-based analysis reduces to switch analysis''. In: '''Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC'15)''', Sendai, Japan, 2015, pp.2603-2610, pp.2603-2610. ([{UP}papers/cec15-sa-ca.pdf|PDF]) * Chao Qian, __Yang Yu__ and Zhi-Hua Zhou. ''Pareto ensemble pruning''. In: '''Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI'15)''', Austin, TX, 2015, pp.2935-2941.([{UP}papers/aaai15-pep.pdf|PDF]) * Chao Qian, __Yang Yu__, Yaochu Jin and Zhi-Hua Zhou. ''On the effectiveness of sampling for evolutionary optimization in noisy environments''. In: '''Proceedings of the 13th International Conference on Parallel Problem Solving from Nature (PPSN’14)''', Ljubljana, Slovenia, 2014, pp.302-311. ([{UP}papers/ppsn14-sampling.pdf|PDF]) * __Yang Yu__ and Qing Da, ''PolicyBoost: Functional policy gradient with ranking-based reward objective''. In: '''Proceedings of AAAI Workshop on AI and Robotics (AIRob'14)''', Quebec City, Canada, 2014, pp.57-62. ([{UP}papers/airob14-pb.pdf|PDF]) * __Yang Yu__, and Hong Qian. ''The sampling-and-learning framework: A statistical view of evolutionary algorithms''. In: '''Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC'14)''', Beijing, China, 2014, pp.149-158. ([{UP}papers/cec14-sal.pdf|PDF]) * Qing Da, __Yang Yu__, and Zhi-Hua Zhou. ''Learning with augmented class by exploiting unlabeled data''. In: '''Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI'14)''', Québec city, Canada, 2014, pp.1760-1766. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/aaai14lacu.pdf|PDF]) * Qing Da, __Yang Yu__, and Zhi-Hua Zhou. ''Napping for functional representation of policy''. In: '''Proceedings of the 2014 International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS'14)''', Paris, France, 2014, pp.189-196. ([{UP}papers/aamas14-nap.pdf|PDF]) ([code_funcpolicy|Code]) * Qing Da, __Yang Yu__, and Zhi-Hua Zhou. ''Self-practice imitation learning from weak policy''. In: '''Proceedings of the 2nd IAPR International Workshop on Partially Supervised Learning (PSL'13)''', Nanjing, China, 2013, pp.9-20. * __Yang Yu__, Xin Yao, and Zhi-Hua Zhou. ''On the approximation ability of evolutionary optimization with application to minimum set cover: Extended abstract''. In: '''Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI'13)''' (Journal Paper Track), Beijing, China, 2013. * Nan Li, __Yang Yu__, and Zhi-Hua Zhou. ''Diversity regularized ensemble pruning''. In: '''Proceedings of the 23rd European Conference on Machine Learning (ECML'12)''', Bristol, U.K., 2012, pp.330-345. ([^{UP}papers/ecml12-divprune.pdf|PDF]) ([^http://lamda.nju.edu.cn/code_DREP.ashx|code]) * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''On algorithm-dependent boundary case identification for problem classes''. In: '''Proceedings of the 12th International Conference on Parallel Problem Solving from Nature (PPSN'12)''' Taormina, Italy, 2012, pp.62-71. ([^{UP}papers/ppsn12-boundary.pdf|PDF]) * Sheng-Jun Huang, __Yang Yu__, and Zhi-Hua Zhou. ''Multi-label hypothesis reuse''. In: '''Proceedings of the 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'12)''', Beijing, China, 2012, pp.525-533. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/kdd12mahr.pdf|PDF]) ([http://lamda.nju.edu.cn/code_MAHR.ashx|code]) <font color="blue">(The poster presentation won the Best Poster Award at KDD'12)</font> * Sheng-Jun Huang, __Yang Yu__ and Zhi-Hua Zhou, ''Multi-label boosting via hypothesis reuse''. In: '''Proceedings of NIPS Workshop on Chanllenges in Learning Hierarchical Models: Transfer Learning and Optimization''', Granada, Spain 2011. * Wang-Zhou Dai, __Yang Yu__, and Zhi-Hua Zhou. ''Lifted-rollout for approximate policy iteration of Markov decision process''. In: '''Proceedings of the International Workshop on Learning and Data Mining for Robotics (LEMIR'11)''', in conjunction with ICDM'11, Vancouver, Canada, 2011. * __Yang Yu__, Yu-Feng Li, and Zhi-Hua Zhou. ''Diversity Regularized Machine'' In: '''Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI'11)''', Barcelona, Spain, 2011, pp. 1603-1608. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/ijcai11drm.pdf|PDF]) ([^http://lamda.nju.edu.cn/code_DRM.ashx|code]) * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''An analysis on recombination in multi-objective evolutionary optimization''. In: '''Proceedings of the 13th ACM Conference on Genetic and Evolutionary Computation (GECCO'11)''', Dublin, Ireland, 2011, pp. 2051-2058. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/gecco11remo.pdf|PDF]) <font color="blue">(This paper won the Best Paper Award of the Theory Track at GECCO'11)</font> * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''Collisions are helpful for computing unique input-output sequences''. In: '''Proceedings of the 13th ACM Conference on Genetic and Evolutionary Computation (GECCO'11)''' (Companion Material/Poster), Dublin, Ireland, 2011, pp. 265-266. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/gecco11uio.pdf|PDF]) * __Yang Yu__, Chao Qian, and Zhi-Hua Zhou. ''Towards analyzing recombination operators in evolutionary search''. In: '''Proceedings of the 11th International Conference on Parallel Problem Solving from Nature (PPSN'10)''' Part I, Krakow, Poland, 2010, pp.144-153. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/ppsn10crossover.pdf|PDF]) * Nan Li, __Yang Yu__, and Zhi-Hua Zhou. ''Semi-naive exploitation of one-dependence estimators''. In: '''Proceedings of the 9th IEEE International Conference on Data Mining (ICDM'09)''', Miami, FL, 2009, pp.278-287. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/icdm09a.pdf|PDF]) * __Yang Yu__ and Zhi-Hua Zhou. ''A framework for modeling positive class expansion with single snapshot''. In: '''Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'08)''', Osaka, Japan, LNAI 5012, 2008, pp.429-440. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/pakdd08a.pdf|PDF]) ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/annex/pakdd08aslides.pdf|slides]) <font color="blue">(This paper won the Best Paper Award at PAKDD'08)</font> * __Yang Yu__ and Zhi-Hua Zhou. ''On the usefulness of infeasible solutions in evolutionary search: A theoretical study''. In: '''Proceedings of the IEEE Congress on Evolutionary Computation (CEC'08)''', Hong Kong, China, 2008, pp.835-840. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/cec08.pdf|PDF]) * Li-Ping Liu, __Yang Yu__, Yuan Jiang, and Zhi-Hua Zhou. ''TEFE: A time-efficient approach to feature extraction''. In: '''Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08)''', Pisa, Italy, 2008, pp.423-432. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/icdm08c.pdf|PDF]) * __Yang Yu__, Zhi-Hua Zhou, and Kai Ming Ting. ''Cocktail ensemble for regression''. In: '''Proceedings of the 7th IEEE International Conference on Data Mining (ICDM'07)''', Omaha, NE, 2007, pp.721-726. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/icdm07.pdf|PDF]) * __Yang Yu__ and Zhi-Hua Zhou. ''A new approach to estimating the expected first hitting time of evolutionary algorithms''. In: '''Proceedings of the 21st National Conference on Artificial Intelligence (AAAI'06)''', Boston, MA, 2006, pp.555-560. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/aaai06b.pdf|PDF]) ===Journal Articles=== * Chao Qian, Chao Bian, __Yang Yu__, Ke Tang, and Xin Yao. ''Analysis of noisy evolutionary optimization when sampling fails''. '''Algorithmica''', in press. * Chao Qian, __Yang Yu__, Ke Tang, Xin Yao, Zhi-Hua Zhou. ''Maximizing submodular or monotone approximately submodular functions by multi-objective evolutionary algorithms''. '''Artificial Intelligence''', 2019, 275: 279-294. * __Yang Yu__, Shi-Yong Chen, Qing Da, Zhi-Hua Zhou. ''Reusable reinforcement learning via shallow trails''. '''IEEE Transactions on Neural Networks and Learning Systems''', 2018, 29(6): 2204-2215.[^{UP}papers/tnnls18-maple.pdf|(Preprint PDF)] * Chao Qian, __Yang Yu__, Ke Tang, Yaochu Jin, Xin Yao, and Zhi-Hua Zhou. ''On the effectiveness of sampling for evolutionary optimization in noisy environments''. '''Evolutionary Computation''', 2018, 26(2): 237-267. [^{UP}papers/ecj17-sampling.pdf|(Preprint PDF)] [^{UP}papers/ecj17-sampling-sup.pdf|(Supplementary)] * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''Analyzing evolutionary optimization in noisy environments''. '''Evolutionary Computation''', 2018, 26(1): 1–41. [^{UP}papers/ecj16-noise.pdf|(Preprint PDF)] * __Yang Yu__, Chao Qian, and Zhi-Hua Zhou. ''Switch analysis for running time analysis of evolutionary algorithms''. '''IEEE Transactions on Evolutionary Computation''', 2015, 19(6):777-792. [^{UP}papers/tec15-switch.pdf|(Preprint PDF)] * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''Variable solution structure can be helpful in evolutionary optimization''. '''Science China: Information Sciences''', 2015, 58(11): 1-17. [^{UP}papers/scis16-gp.pdf|(Preprint PDF)] * Chaoli Sun, Yaochu Jin, Jianchao Zeng, and __Yang Yu__. ''[^http://link.springer.com/article/10.1007/s00500-014-1283-z|A two-layer surrogate-assisted particle swarm optimization algorithm]''. '''Soft Computing''',19(6):1461-1475, 2015. * Chao Qian, __Yang Yu__, and Zhi-Hua Zhou. ''An analysis on recombination in multi-objective evolutionary optimization''. '''Artificial Intelligence''', 2013, 204:99-119. (Extended from GECCO'11) [^{UP}papers/aij13-mocrossover.pdf|(Preprint PDF)] * __Yang Yu__, Xin Yao, and Zhi-Hua Zhou. ''On the approximation ability of evolutionary optimization with application to minimum set cover''. '''Artificial Intelligence''', 2012, 180-181:20-33. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/aij12EAprx.pdf|Preprint PDF]) ([^http://arxiv.org/abs/1011.4028|CORR abs/1011.4028]) * __Yang Yu__ and Zhi-Hua Zhou. ''A framework for modeling positive class expansion with single snapshot''. '''Knowledge and Information Systems''', 2010, 25(2):211-227. (Extended from PAKDD'08) ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/kais10pakdd.pdf|Preprint PDF]) ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/annex/pakdd08aslides.pdf|slides]) ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/annex/SGBDota.htm|code&data]) * __Yang Yu__ and Zhi-Hua Zhou. ''A new approach to estimating the expected first hitting time of evolutionary algorithms''. '''Artificial Intelligence''', 2008, 172(15): 1809-1832. (Extended from AAAI'06) ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/aij08.pdf|Preprint PDF]) * Fei Tony Liu, Kai Ming Ting, __Yang Yu__, and Zhi-Hua Zhou . ''Spectrum of variable-random trees''. '''Journal of Artificial Intelligence Research''', 2008, 32:355-384. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/jair08.pdf|Preprint PDF]) * __Yang Yu__, De-Chuan. Zhan, Xu-Ying Liu, Ming Li, and Zhi-Hua Zhou. ''Predicting future customers via ensembling gradually expanded trees''. '''International Journal of Data Warehousing and Mining''', 2007 3(2): 12-21. <font color="blue">(Invited paper for the PAKDD'06 Data Mining Competition (Open Category) Grand Champion Team)</font> ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/ijdwm07.pdf|Preprint PDF]) * Zhi-Hua Zhou and __Yang Yu__. ''Ensembling local learners through multi-modal perturbation''. '''IEEE Transactions on System, Man, And Cybernetics - Part B: Cybernetics''', 2005, 35(4): 725-735. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/tsmcb05.pdf|Preprint PDF]) ([^http://lamda.nju.edu.cn/code_FASBIR.ashx|code]) * Zhi-Hua Zhou and __Yang Yu__. ''Adapt bagging to nearest neighbor classifiers''. '''Journal of Computer Science and Technology''', 2005, vol.20, no.1 pp.48-54. ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/jcst05.pdf|Preprint PDF]) ([^http://cs.nju.edu.cn/zhouzh/zhouzh.files/publication/annex/jcst05-expdata.rar|detailed result]) ===Thesis=== * __Yang Yu__. '''Evolutionary Computation: Theoretical Analysis and Learning Algorithms'''. Ph.D. Dissertation, 2011. * __Yang Yu__. '''Local Validity Based Selective Ensemble of Decision Trees'''. B.Sc. Thesis, 2004. (in Chinese with English abstract) ([^http://lamda.nju.edu.cn/yuy/files/BSc.thesis.pdf|PDF])
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