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ORCIDJiabin Lin
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2020 – today
- 2024
[j6]Jiabin Lin, Shana Moothedath
:
Fast and Sample-Efficient Relevance-Based Multi-Task Representation Learning. IEEE Control. Syst. Lett. 8: 1397-1402 (2024)- [j5]Chenquan Gan, Jiabin Lin, Da-Wen Huang, Qingyi Zhu, Liang Tian, Deepak Kumar Jain:
Equipment classification based differential game method for advanced persistent threats in Industrial Internet of Things. Expert Syst. Appl. 236: 121255 (2024) - [c10]Jiabin Lin, Karuna Anna Sajeevan, Bibek Acharya, Shana Moothedath, Ratul Chowdhury:
Distributed Stochastic Contextual Bandits for Protein Drug Interaction. ICASSP 2024: 7160-7164 - [c9]Jiabin Lin, Shana Moothedath, Namrata Vaswani:
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits. ICML 2024 - [c8]Jiabin Lin, Shana Moothedath:
Federated Learning for Heterogeneous Bandits with Unobserved Contexts. ISIT 2024: 2086-2091 - [i6]Jiabin Lin, Shana Moothedath:
Distributed Multi-Task Learning for Stochastic Bandits with Context Distribution and Stage-wise Constraints. CoRR abs/2401.11563 (2024) - [i5]Jiabin Lin, Shana Moothedath, Namrata Vaswani:
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits. CoRR abs/2410.02068 (2024) - 2023
- [c7]Jiabin Lin, Shana Moothedath:
Feature Selection in Distributed Stochastic Linear Bandits. ACC 2023: 3939-3944 - [c6]Jiabin Lin, Shana Moothedath:
Distributed Stochastic Bandit Learning with Delayed Context Observation. ECC 2023: 1-6 - [c5]Jiabin Lin, Shana Moothedath:
Distributed Stochastic Bandits with Hidden Contexts. ECC 2023: 1-6 - [c4]Jiabin Lin, Qi Chen, Bing Xue, Mengjie Zhang:
AMTEA-Based Multi-task Optimisation for Multi-objective Feature Selection in Classification. EvoApplications@EvoStar 2023: 623-639 - [i4]Jiabin Lin, Shana Moothedath:
Federated Stochastic Bandit Learning with Unobserved Context. CoRR abs/2303.17043 (2023) - [i3]Geethu Joseph, Shana Moothedath, Jiabin Lin:
Minimal Input Structural Modifications for Strongly Structural Controllability. CoRR abs/2311.05653 (2023) - 2022
- [j4]Deyou Tang, Daqiang Tan, Weihao Xiao, Jiabin Lin, Juan Fu:
KMC3 and CHTKC: Best Scenarios, Deficiencies, and Challenges in High-Throughput Sequencing Data Analysis. Algorithms 15(4): 107 (2022) - [j3]Deyou Tang, Yucheng Li, Daqiang Tan, Juan Fu, Yelei Tang, Jiabin Lin, Rong Zhao, Hongli Du, Zhongming Zhao:
KCOSS: an ultra-fast k-mer counter for assembled genome analysis. Bioinform. 38(4): 933-940 (2022) - [c3]Jiabin Lin, Xian Yeow Lee, Talukder Z. Jubery, Shana Moothedath, Soumik Sarkar, Baskar Ganapathysubramanian:
Stochastic Conservative Contextual Linear Bandits. CDC 2022: 7321-7326 - [c2]Jiabin Lin, Qi Chen, Bing Xue, Mengjie Zhang:
Multi-task optimisation for multi-objective feature selection in classification. GECCO Companion 2022: 264-267 - [i2]Jiabin Lin, Xian Yeow Lee, Talukder Z. Jubery, Shana Moothedath, Soumik Sarkar, Baskar Ganapathysubramanian:
Stochastic Conservative Contextual Linear Bandits. CoRR abs/2203.15629 (2022) - [i1]Jiabin Lin, Shana Moothedath:
Distributed Stochastic Bandit Learning with Context Distributions. CoRR abs/2207.14391 (2022) - 2021
- [j2]Jiabin Lin, Hai-Lin Liu, Kay Chen Tan, Fangqing Gu:
An Effective Knowledge Transfer Approach for Multiobjective Multitasking Optimization. IEEE Trans. Cybern. 51(6): 3238-3248 (2021) - 2020
- [j1]Jiabin Lin, Hai-Lin Liu, Bing Xue, Mengjie Zhang, Fangqing Gu:
Multiobjective Multitasking Optimization Based on Incremental Learning. IEEE Trans. Evol. Comput. 24(5): 824-838 (2020)
2010 – 2019
- 2017
- [c1]Jiabin Lin, Hai-Lin Liu, Chaoda Peng:
The Effect of Feasible Region on Imbalanced Problem in Constrained Multi-objective Optimization. CIS 2017: 82-86
Coauthor Index
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