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Manuscripts
Yu-Ren Liu, Yi-Qi Hu, Hong Qian,
Yang Yu
, and Chao Qian.
ZOOpt: Toolbox for derivative-free optimization
.
arXiv:1801.00329
, 2018.
Edit
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) (
Springer Link
)
Edit
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. (
PDF
)
Edit
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. (
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. (
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. (
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. (
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. (
PDF
) (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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.
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
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. (
PDF
)(
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. (
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. (
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. (
PDF
) (
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. (
PDF
) (
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. (
PDF
) (
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. (
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. (
PDF with Appendix
) (
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. (
PDF
)
(This paper won a Best Paper Award of IDEAL'16)
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. (
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. (
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. (
PDF
) (
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. (
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. (
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. (
PDF
) (
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. (
PDF
) (
Appendix
) (
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. (
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. (
PDF
) (
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. (
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. (
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.(
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. (
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. (
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. (
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. (
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. (
PDF
) (
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. (
PDF
) (
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. (
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. (
PDF
) (
code
)
(The poster presentation won the Best Poster Award at KDD'12)
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. (
PDF
) (
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. (
PDF
)
(This paper won the Best Paper Award of the Theory Track at GECCO'11)
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. (
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. (
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. (
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. (
PDF
) (
slides
)
(This paper won the Best Paper Award at PAKDD'08)
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. (
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. (
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. (
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. (
PDF
)
Edit
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.
(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.
(Preprint PDF)
(Supplementary)
Chao Qian,
Yang Yu
, and Zhi-Hua Zhou.
Analyzing evolutionary optimization in noisy environments
.
Evolutionary Computation
, 2018, 26(1): 1–41.
(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.
(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.
(Preprint PDF)
Chaoli Sun, Yaochu Jin, Jianchao Zeng, and
Yang Yu
.
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)
(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. (
Preprint PDF
) (
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) (
Preprint PDF
) (
slides
) (
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) (
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. (
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.
(Invited paper for the PAKDD'06 Data Mining Competition (Open Category) Grand Champion Team)
(
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. (
Preprint PDF
) (
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. (
Preprint PDF
) (
detailed result
)
Edit
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) (
PDF
)
The end