Chao Qian
标题
引用次数
引用次数
年份
Subset selection by Pareto optimization
C Qian, Y Yu, ZH Zhou
Advances in neural information processing systems 28, 1774-1782, 2015
1062015
Pareto ensemble pruning
C Qian, Y Yu, ZH Zhou
Twenty-ninth AAAI conference on artificial intelligence, 2015
892015
An analysis on recombination in multi-objective evolutionary optimization
C Qian, Y Yu, ZH Zhou
Artificial Intelligence 204, 99-119, 2013
792013
On the effectiveness of sampling for evolutionary optimization in noisy environments
C Qian, Y Yu, K Tang, Y Jin, X Yao, ZH Zhou
Evolutionary computation 26 (2), 237-267, 2018
48*2018
Analyzing evolutionary optimization in noisy environments
C Qian, Y Yu, ZH Zhou
Evolutionary computation 26 (1), 1-41, 2018
382018
Subset Selection under Noise.
C Qian, JC Shi, Y Yu, K Tang, ZH Zhou
NIPS, 3560-3570, 2017
382017
On Subset Selection with General Cost Constraints.
C Qian, JC Shi, Y Yu, K Tang
IJCAI 17, 2613-2619, 2017
362017
Selection hyper-heuristics can provably be helpful in evolutionary multi-objective optimization
C Qian, K Tang, ZH Zhou
International Conference on Parallel Problem Solving from Nature, 835-846, 2016
342016
Parallel Pareto Optimization for Subset Selection.
C Qian, JC Shi, Y Yu, K Tang, ZH Zhou
IJCAI, 1939-1945, 2016
332016
Switch analysis for running time analysis of evolutionary algorithms
Y Yu, C Qian, ZH Zhou
IEEE Transactions on Evolutionary Computation 19 (6), 777-792, 2014
312014
Evolutionary learning: Advances in theories and algorithms
ZH Zhou, Y Yu, C Qian
Springer Singapore, 2019
30*2019
Constrained Monotone-Submodular Function Maximization Using Multiobjective Evolutionary Algorithms With Theoretical Guarantee
C Qian, JC Shi, K Tang, ZH Zhou
IEEE Transactions on Evolutionary Computation 22 (4), 595-608, 2017
282017
Optimization based Layer-wise Magnitude-based Pruning for DNN Compression.
G Li, C Qian, C Jiang, X Lu, K Tang
IJCAI, 2383-2389, 2018
272018
On constrained boolean pareto optimization
C Qian, Y Yu, ZH Zhou
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
272015
Running Time Analysis of the ( 1 + 1 )-EA for OneMax and LeadingOnes Under Bit-Wise Noise
C Qian, C Bian, W Jiang, K Tang
Algorithmica 81 (2), 749-795, 2019
222019
Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error.
C Jiang, G Li, C Qian, K Tang
IJCAI 2018, 2-2, 2018
212018
Maximizing submodular or monotone approximately submodular functions by multi-objective evolutionary algorithms
C Qian, Y Yu, K Tang, X Yao, ZH Zhou
Artificial Intelligence 275, 279-294, 2019
19*2019
Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection.
C Qian, Y Yu, K Tang
IJCAI, 1478-1484, 2018
182018
Variable solution structure can be helpful in evolutionary optimization
C Qian, Y Yu, ZH Zhou
Science China Information Sciences 58 (11), 1-17, 2015
172015
Unsupervised feature selection by Pareto optimization
C Feng, C Qian, K Tang
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3534-3541, 2019
162019
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