The Effect of Feasible Region on Imbalanced Problem in Constrained Multi-objective Optimization. - Jiabin Lin; Hai-Lin Liu 001; Chaoda Peng (CIS, 2017)

Multiobjective Multitasking Optimization Based on Incremental Learning. - Jiabin Lin; Hai-Lin Liu 001; Bing Xue 001; Mengjie Zhang 001; Fangqing Gu (IEEE Trans. Evol. Comput., 2020)

An Effective Knowledge Transfer Approach for Multiobjective Multitasking Optimization. - Jiabin Lin; Hai-Lin Liu 001; Kay Chen Tan; Fangqing Gu (IEEE Trans. Cybern., 2021)

Stochastic Conservative Contextual Linear Bandits. - Jiabin Lin; Xian Yeow Lee; Talukder Z. Jubery; Shana Moothedath; Soumik Sarkar; Baskar Ganapathysubramanian (CDC, 2022)

Multi-task optimisation for multi-objective feature selection in classification. - Jiabin Lin; Qi Chen 002; Bing Xue 001; Mengjie Zhang 001 (GECCO Companion, 2022)

KMC3 and CHTKC: Best Scenarios, Deficiencies, and Challenges in High-Throughput Sequencing Data Analysis. - Deyou Tang; Daqiang Tan; Weihao Xiao; Jiabin Lin; Juan Fu (Algorithms, 2022)

KCOSS: an ultra-fast k-mer counter for assembled genome analysis. - Deyou Tang; Yucheng Li; Daqiang Tan; Juan Fu; Yelei Tang; Jiabin Lin; Rong Zhao; Hongli Du; Zhongming Zhao (Bioinform., 2022)

Distributed Stochastic Bandit Learning with Context Distributions. - Jiabin Lin; Shana Moothedath (CoRR, 2022)

Feature Selection in Distributed Stochastic Linear Bandits. - Jiabin Lin; Shana Moothedath (ACC, 2023)

Distributed Stochastic Bandit Learning with Delayed Context Observation. - Jiabin Lin; Shana Moothedath (ECC, 2023)

Distributed Stochastic Bandits with Hidden Contexts. - Jiabin Lin; Shana Moothedath (ECC, 2023)

AMTEA-Based Multi-task Optimisation for Multi-objective Feature Selection in Classification. - Jiabin Lin; Qi Chen 002; Bing Xue 001; Mengjie Zhang 001 (EvoApplications@EvoStar, 2023)

Federated Stochastic Bandit Learning with Unobserved Context. - Jiabin Lin; Shana Moothedath (CoRR, 2023)

Analysis of Computer Virus Propagation in Social Internet of Things. - Luis Martes Calderon; Chenquan Gan; Jiabin Lin; Wei Yang 006; Deepak Kumar Jain 001 (ADMA (1), 2024)

Minimal Input Structural Modifications for Strongly Structural Controllability. - Geethu Joseph; Shana Moothedath; Jiabin Lin (CDC, 2024)

Distributed Stochastic Contextual Bandits for Protein Drug Interaction. - Jiabin Lin; Karuna Anna Sajeevan; Bibek Acharya; Shana Moothedath; Ratul Chowdhury (ICASSP, 2024)

Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits. - Jiabin Lin; Shana Moothedath; Namrata Vaswani (ICML, 2024)

Federated Learning for Heterogeneous Bandits with Unobserved Contexts. - Jiabin Lin; Shana Moothedath (ISIT, 2024)

Fast and Sample-Efficient Relevance-Based Multi-Task Representation Learning. - Jiabin Lin; Shana Moothedath (IEEE Control. Syst. Lett., 2024)

Equipment classification based differential game method for advanced persistent threats in Industrial Internet of Things. - Chenquan Gan; Jiabin Lin; Da-Wen Huang; Qingyi Zhu; Liang Tian; Deepak Kumar Jain 001 (Expert Syst. Appl., 2024)

Evolutionary Multitasking for Multiobjective Feature Selection in Classification. - Jiabin Lin; Qi Chen 002; Bing Xue 001; Mengjie Zhang 001 (IEEE Trans. Evol. Comput., 2024)

Analysis of attack-defense game for advanced malware propagation control in cloud. - Liang Tian; Chenquan Gan; Jiabin Lin; Fengjun Shang; Qingyi Zhu (Comput. Commun., 2025)

Distributed Multi-Task Learning for Stochastic Bandits With Context Distribution and Stage-Wise Constraints. - Jiabin Lin; Shana Moothedath (IEEE Trans. Signal Inf. Process. over Networks, 2025)

Evolutionary Sequential Transfer Learning for Multi-Objective Feature Selection in Classification. - Jiabin Lin; Qi Chen 002; Bing Xue 001; Mengjie Zhang 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2025)