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Chao Qian
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Cited by
Year
Subset selection by Pareto optimization
C Qian, Y Yu, ZH Zhou
Advances in neural information processing systems 28, 2015
1792015
Evolutionary learning: Advances in theories and algorithms
ZH Zhou, Y Yu, C Qian
Springer Singapore, 2019
1202019
Pareto ensemble pruning
C Qian, Y Yu, ZH Zhou
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
1202015
An analysis on recombination in multi-objective evolutionary optimization
C Qian, Y Yu, ZH Zhou
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
1082011
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
71*2018
Subset selection under noise
C Qian, JC Shi, Y Yu, K Tang, ZH Zhou
Advances in neural information processing systems 30, 2017
712017
Optimization based Layer-wise Magnitude-based Pruning for DNN Compression.
G Li, C Qian, C Jiang, X Lu, K Tang
IJCAI 330, 2383-2389, 2018
672018
On Subset Selection with General Cost Constraints.
C Qian, JC Shi, Y Yu, K Tang
IJCAI 17, 2613-2619, 2017
642017
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
572017
Analyzing evolutionary optimization in noisy environments
C Qian, Y Yu, ZH Zhou
Evolutionary computation 26 (1), 1-41, 2018
542018
Parallel Pareto Optimization for Subset Selection.
C Qian, JC Shi, Y Yu, K Tang, ZH Zhou
IJCAI, 1939-1945, 2016
512016
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
482016
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
462019
Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error.
C Jiang, G Li, C Qian, K Tang
IJCAI 2018, 2-2, 2018
452018
On constrained boolean pareto optimization
C Qian, Y Yu, ZH Zhou
Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015
432015
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
402014
Distributed Pareto optimization for large-scale noisy subset selection
C Qian
IEEE Transactions on Evolutionary Computation 24 (4), 694-707, 2019
362019
Running time analysis of the (1+ 1)-EA for OneMax and LeadingOnes under bit-wise noise
C Qian, C Bian, W Jiang, K Tang
Proceedings of the Genetic and Evolutionary Computation Conference, 1399-1406, 2017
332017
Better running time of the non-dominated sorting genetic algorithm II (NSGA-II) by using stochastic tournament selection
C Bian, C Qian
International Conference on Parallel Problem Solving from Nature, 428-441, 2022
32*2022
An efficient evolutionary algorithm for subset selection with general cost constraints
C Bian, C Feng, C Qian, Y Yu
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3267-3274, 2020
302020
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