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Journal Articles
- 2025
[j15]Jiahao Wu
, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, Ke Tang:
Condensing Pre-Augmented Recommendation Data via Lightweight Policy Gradient Estimation. IEEE Trans. Knowl. Data Eng. 37(1): 162-173 (2025)- 2024
- [j14]Yuhan Dai, Zhirui Zhang, Yichao Du, Shengcai Liu, Lemao Liu, Tong Xu:
Datastore Distillation for Nearest Neighbor Machine Translation. IEEE ACM Trans. Audio Speech Lang. Process. 32: 807-817 (2024) - [j13]Xuanfeng Li, Shengcai Liu, Jin Wang, Xiao Chen, Yew-Soon Ong, Ke Tang:
Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. IEEE Trans. Cybern. 54(12): 7969-7980 (2024) - [j12]Shengcai Liu, Ning Lu, Wenjing Hong, Chao Qian, Ke Tang:
Effective and Imperceptible Adversarial Textual Attack Via Multi-objectivization. ACM Trans. Evol. Learn. Optim. 4(3): 16:1-16:23 (2024) - [j11]Ning Lu, Shengcai Liu, Rui He, Yew-Soon Ong, Qi Wang, Ke Tang:
Large Language Models can be Guided to Evade AI-generated Text Detection. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [j10]Shengcai Liu, Yu Zhang, Ke Tang, Xin Yao:
How Good is Neural Combinatorial Optimization? A Systematic Evaluation on the Traveling Salesman Problem. IEEE Comput. Intell. Mag. 18(3): 14-28 (2023) - [j9]Yongfan Lu, Bingdong Li, Shengcai Liu, Aimin Zhou:
A Population Cooperation based Particle Swarm Optimization algorithm for large-scale multi-objective optimization. Swarm Evol. Comput. 83: 101377 (2023) - [j8]Rui He, Shengcai Liu, Shan He, Ke Tang:
Multi-Domain Active Learning: Literature Review and Comparative Study. IEEE Trans. Emerg. Top. Comput. Intell. 7(3): 791-804 (2023) - [j7]Zeyu Dai, Shengcai Liu, Qing Li, Ke Tang:
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. ACM Trans. Intell. Syst. Technol. 14(3): 45:1-45:20 (2023) - 2022
- [j6]Shengcai Liu, Ning Lu, Cheng Chen, Ke Tang:
Efficient Combinatorial Optimization for Word-Level Adversarial Textual Attack. IEEE ACM Trans. Audio Speech Lang. Process. 30: 98-111 (2022) - [j5]Shengcai Liu, Ke Tang, Xin Yao:
Generative Adversarial Construction of Parallel Portfolios. IEEE Trans. Cybern. 52(2): 784-795 (2022) - 2021
- [j4]Minshi Chen, Jianxun Chen, Peng Yang, Shengcai Liu, Ke Tang:
A heuristic repair method for dial-a-ride problem in intracity logistic based on neighborhood shrinking. Multim. Tools Appl. 80(20): 30775-30787 (2021) - [j3]Shengcai Liu, Ke Tang, Xin Yao:
Memetic search for vehicle routing with simultaneous pickup-delivery and time windows. Swarm Evol. Comput. 66: 100927 (2021) - [j2]Ke Tang, Shengcai Liu, Peng Yang, Xin Yao:
Few-Shots Parallel Algorithm Portfolio Construction via Co-Evolution. IEEE Trans. Evol. Comput. 25(3): 595-607 (2021) - 2016
- [j1]Shengcai Liu, Jiang-She Zhang, Junmin Liu, Qingyan Yin:
ℓ1/2, 1 group sparse regularization for compressive sensing. Signal Image Video Process. 10(5): 861-868 (2016)
Conference and Workshop Papers
- 2024
- [c10]Shengcai Liu, Caishun Chen, Xinghua Qu, Ke Tang, Yew-Soon Ong:
Large Language Models as Evolutionary Optimizers. CEC 2024: 1-8 - 2023
- [c9]Shengcai Liu, Fu Peng, Ke Tang:
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. AAAI 2023: 8852-8860 - [c8]Shaofeng Zhang, Shengcai Liu, Ke Tang:
A Sample Reuse Strategy for Dynamic Influence Maximization Problem. BIC-TA (2) 2023: 107-120 - [c7]Rui He, Shengcai Liu, Jiahao Wu, Shan He, Ke Tang:
Multi-Domain Learning from Insufficient Annotations. ECAI 2023: 1028-1035 - 2022
- [c6]Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qing Li, Ke Tang:
Disentangled Contrastive Learning for Social Recommendation. CIKM 2022: 4570-4574 - [c5]Fu Peng, Shengcai Liu, Ning Lu, Ke Tang:
Training Quantized Deep Neural Networks via Cooperative Coevolution. ICSI (2) 2022: 81-93 - 2021
- [c4]Kangfei Zhao, Shengcai Liu, Jeffrey Xu Yu, Yu Rong:
Towards Feature-free TSP Solver Selection: A Deep Learning Approach. IJCNN 2021: 1-8 - 2020
- [c3]Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao:
On Performance Estimation in Automatic Algorithm Configuration. AAAI 2020: 2384-2391 - 2019
- [c2]Shengcai Liu, Ke Tang, Xin Yao:
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. AAAI 2019: 1560-1567 - 2015
- [c1]Shengcai Liu, Yufan Wei, Ke Tang, A. Kai Qin, Xin Yao:
QoS-aware long-term based service composition in cloud computing. CEC 2015: 3362-3369
Informal and Other Publications
- 2024
- [i30]Yongfan Lu, Zixiang Di, Bingdong Li, Shengcai Liu, Hong Qian, Peng Yang, Ke Tang, Aimin Zhou:
Towards Geometry-Aware Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization. CoRR abs/2405.08604 (2024) - [i29]Shengcai Liu, Zhiyuan Wang, Yew-Soon Ong, Xin Yao, Ke Tang:
Learning Mixture-of-Experts for General-Purpose Black-Box Discrete Optimization. CoRR abs/2405.18884 (2024) - [i28]Jiahao Wu, Ning Lu, Zeiyu Dai, Wenqi Fan, Shengcai Liu, Qing Li, Ke Tang:
Backdoor Graph Condensation. CoRR abs/2407.11025 (2024) - [i27]Zubin Zheng, Shengcai Liu, Yew-Soon Ong:
Hybrid Memetic Search for Electric Vehicle Routing with Time Windows, Simultaneous Pickup-Delivery, and Partial Recharges. CoRR abs/2410.19580 (2024) - 2023
- [i26]Ning Lu, Shengcai Liu, Zhirui Zhang, Qi Wang, Haifeng Liu, Ke Tang:
Less is More: Understanding Word-level Textual Adversarial Attack via n-gram Frequency Descend. CoRR abs/2302.02568 (2023) - [i25]Rui He, Shengcai Liu, Jiahao Wu, Shan He, Ke Tang:
Multi-Domain Learning From Insufficient Annotations. CoRR abs/2305.02757 (2023) - [i24]Ning Lu, Shengcai Liu, Rui He, Qi Wang, Ke Tang:
Large Language Models can be Guided to Evade AI-Generated Text Detection. CoRR abs/2305.10847 (2023) - [i23]Xuanfeng Li, Shengcai Liu, Jin Wang, Xiao Chen, Yew-Soon Ong, Ke Tang:
Data-Driven Chance-Constrained Multiple-Choice Knapsack Problem: Model, Algorithms, and Applications. CoRR abs/2306.14690 (2023) - [i22]Wenjie Chen, Shengcai Liu, Yew-Soon Ong, Ke Tang:
Neural Influence Estimator: Towards Real-time Solutions to Influence Blocking Maximization. CoRR abs/2308.14012 (2023) - [i21]Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Qing Li, Ke Tang:
Enhancing Graph Collaborative Filtering via Uniformly Co-Clustered Intent Modeling. CoRR abs/2309.12723 (2023) - [i20]Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, Ke Tang:
Dataset Condensation for Recommendation. CoRR abs/2310.01038 (2023) - [i19]Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao-Ming Wu, Ke Tang:
Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation. CoRR abs/2310.09874 (2023) - [i18]Shengcai Liu, Caishun Chen, Xinghua Qu, Ke Tang, Yew-Soon Ong:
Large Language Models as Evolutionary Optimizers. CoRR abs/2310.19046 (2023) - [i17]Shaofeng Zhang, Shengcai Liu, Ke Tang:
A Sample Reuse Strategy for Dynamic Influence Maximization Problem. CoRR abs/2311.15345 (2023) - [i16]Muyao Zhong, Shengcai Liu, Bingdong Li, Haobo Fu, Ke Tang, Peng Yang:
Pointer Networks Trained Better via Evolutionary Algorithms. CoRR abs/2312.01150 (2023) - 2022
- [i15]Zeyu Dai, Shengcai Liu, Ke Tang, Qing Li:
Saliency Attack: Towards Imperceptible Black-box Adversarial Attack. CoRR abs/2206.01898 (2022) - [i14]Jiahao Wu, Wenqi Fan, Jingfan Chen, Shengcai Liu, Qing Li, Ke Tang:
Disentangled Contrastive Learning for Social Recommendation. CoRR abs/2208.08723 (2022) - [i13]Shengcai Liu, Yu Zhang, Ke Tang, Xin Yao:
How Good Is Neural Combinatorial Optimization? CoRR abs/2209.10913 (2022) - [i12]Xiasheng Ma, Shengcai Liu, Wenjing Hong:
Automatic Construction of Parallel Algorithm Portfolios for Multi-objective Optimization. CoRR abs/2211.09498 (2022) - [i11]Shengcai Liu, Fu Peng, Ke Tang:
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles. CoRR abs/2211.12713 (2022) - 2021
- [i10]Wenjie Chen, Shengcai Liu, Ke Tang:
A New Knowledge Gradient-based Method for Constrained Bayesian Optimization. CoRR abs/2101.08743 (2021) - [i9]Shengcai Liu, Ning Lu, Cheng Chen, Ke Tang:
Efficient Combinatorial Optimization for Word-level Adversarial Textual Attack. CoRR abs/2109.02229 (2021) - [i8]Shengcai Liu, Ning Lu, Cheng Chen, Chao Qian, Ke Tang:
HydraText: Multi-objective Optimization for Adversarial Textual Attack. CoRR abs/2111.01528 (2021) - [i7]Fu Peng, Shengcai Liu, Ke Tang:
Training Quantized Deep Neural Networks via Cooperative Coevolution. CoRR abs/2112.14834 (2021) - 2020
- [i6]Kangfei Zhao, Shengcai Liu, Yu Rong, Jeffrey Xu Yu:
Leveraging TSP Solver Complementarity via Deep Learning. CoRR abs/2006.00715 (2020) - [i5]Ke Tang, Shengcai Liu, Peng Yang, Xin Yao:
Few-shots Parameter Tuning via Co-evolution. CoRR abs/2007.00501 (2020) - [i4]Shengcai Liu, Ke Tang, Xin Yao:
Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows. CoRR abs/2011.06331 (2020) - 2019
- [i3]Shengcai Liu, Ke Tang, Yunwen Lei, Xin Yao:
On Performance Estimation in Automatic Algorithm Configuration. CoRR abs/1911.08200 (2019) - 2018
- [i2]Shengcai Liu, Ke Tang, Xin Yao:
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping. CoRR abs/1804.06088 (2018) - 2017
- [i1]Shengcai Liu, Ke Tang, Xin Yao:
Experience-based Optimization: A Coevolutionary Approach. CoRR abs/1703.09865 (2017)
Coauthor Index
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