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Journal Articles
- 2024
[j10]Ngoc Hoang Luong
, Quan Minh Phan, An Vo, Tan Ngoc Pham, Dzung Tri Bui:
Lightweight multi-objective evolutionary neural architecture search with low-cost proxy metrics. Inf. Sci. 655: 119856 (2024)- [j9]Quan Minh Phan, Ngoc Hoang Luong:
Parameter-less Pareto local search for multi-objective neural architecture search with the Interleaved Multi-start Scheme. Swarm Evol. Comput. 87: 101573 (2024) - 2023
- [j8]Quan Minh Phan, Ngoc Hoang Luong:
Enhancing multi-objective evolutionary neural architecture search with training-free Pareto local search. Appl. Intell. 53(8): 8654-8672 (2023) - [j7]An Vo, Tan Ngoc Pham, Van Bich Nguyen, Ngoc Hoang Luong:
Lightweight Multi-Objective and Many-Objective Problem Formulations for Evolutionary Neural Architecture Search with the Training-Free Performance Metric Synaptic Flow. Informatica (Slovenia) 47(3) (2023) - 2022
- [j6]Arthur Guijt, Ngoc Hoang Luong, Peter A. N. Bosman, Mathijs de Weerdt:
On the impact of linkage learning, gene-pool optimal mixing, and non-redundant encoding on permutation optimization. Swarm Evol. Comput. 70: 101044 (2022) - 2019
- [j5]Ngoc Hoang Luong, Tanja Alderliesten, Bradley R. Pieters, Arjan Bel, Yury Niatsetski, Peter A. N. Bosman:
Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. Appl. Soft Comput. 84 (2019) - 2018
- [j4]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning. Evol. Comput. 26(3) (2018) - [j3]Ngoc Hoang Luong, Tanja Alderliesten, Arjan Bel, Yury Niatsetski, Peter A. N. Bosman:
Application and benchmarking of multi-objective evolutionary algorithms on high-dose-rate brachytherapy planning for prostate cancer treatment. Swarm Evol. Comput. 40: 37-52 (2018) - [j2]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Multi-objective Gene-pool Optimal Mixing Evolutionary Algorithm with the Interleaved Multi-start Scheme. Swarm Evol. Comput. 40: 238-254 (2018) - 2012
- [j1]Ngoc Hoang Luong, Hai Thanh Thi Nguyen, Chang Wook Ahn:
Entropy-based efficiency enhancement techniques for evolutionary algorithms. Inf. Sci. 188: 100-120 (2012)
Conference and Workshop Papers
- 2024
- [c45]Nhat Minh Le, An Vo, Ngoc Hoang Luong:
Zero-Cost Proxy-Based Hierarchical Initialization for Evolutionary Neural Architecture Search. CEC 2024: 1-8 - [c44]Thai Bao Tran, Ngoc Hoang Luong:
Evolutionary Deep Reinforcement Learning via Hybridizing Estimation-of-Distribution Algorithms with Policy Gradients. CEC 2024: 1-8 - [c43]Quan Minh Phan, Ngoc Hoang Luong:
Efficient Multi-Fidelity Neural Architecture Search with Zero-Cost Proxy-Guided Local Search. GECCO 2024 - [c42]Tri Phan, Khang Tran, Ngoc Hoang Luong:
Combining Adaptive Large Neighborhood Search with Guided Ejection Search for Real-World Multiple-Vehicle Pickup and Delivery Problem with Time Windows. GECCO Companion 2024: 203-206 - [c41]Tran Hai Thanh, Long Doan, Ngoc Hoang Luong, Huynh Thi Thanh Binh:
THNAS-GA: A Genetic Algorithm for Training-free Hardware-aware Neural Architecture Search. GECCO 2024 - [c40]Thai Bao Tran, Ngoc Hoang Luong:
On the Investigation of Multimodal Evolutionary Algorithms Using Search Trajectory Networks. GECCO 2024 - [c39]An Vo, Ngoc Hoang Luong:
Efficient Multi-Objective Neural Architecture Search via Pareto Dominance-based Novelty Search. GECCO 2024 - [c38]Quan Minh Phan, Hieu Trung Nguyen, Van Bich Nguyen, Ngoc Hoang Luong:
Evaluating the Adversarial Robustness of Evolutionary Neural Architecture Search. MAPR 2024: 1-6 - 2023
- [c37]Khoa Huu Tran, Luc Truong, An Vo, Ngoc Hoang Luong:
Accelerating Gene-pool Optimal Mixing Evolutionary Algorithm for Neural Architecture Search with Synaptic Flow. GECCO Companion 2023: 85-86 - [c36]Quan Minh Phan, Ngoc Hoang Luong:
Pareto Local Search is Competitive with Evolutionary Algorithms for Multi-Objective Neural Architecture Search. GECCO 2023: 348-356 - [c35]Hai-Long Tran, Long Doan, Ngoc Hoang Luong, Huynh Thi Thanh Binh:
A Two-Stage Multi-Objective Evolutionary Reinforcement Learning Framework for Continuous Robot Control. GECCO 2023: 577-585 - [c34]Thai Huy Nguyen, Ngoc Hoang Luong:
Stable and Sample-Efficient Policy Search for Continuous Control via Hybridizing Phenotypic Evolutionary Algorithm with the Double Actors Regularized Critics. GECCO 2023: 1239-1247 - [c33]Huy M. Le, Vy T. Luong, Ngoc Hoang Luong:
Data Augmentation with Large Language Models for Vietnamese Abstractive Text Summarization. MAPR 2023: 1-6 - [c32]Khoi Dinh Tran, Dat Viet Bui, Ngoc Hoang Luong:
Evolving Prompts for Synthetic Image Generation with Genetic Algorithm. MAPR 2023: 1-6 - [c31]Quan Minh Phan, Ngoc Hoang Luong:
Enhancing Training-Free Multi-Objective Pruning-Based Neural Architecture Search with Low-Cost Local Search. RIVF 2023: 71-76 - [c30]Hieu-Hien Mai, Ngoc Hoang Luong:
Data Augmentation with GPT-3.5 for Vietnamese Natural Language Inference. RIVF 2023: 435-440 - [c29]Doan Thai Binh Phan, Phuoc Vinh Linh Le, Ngoc Hoang Luong, M. Tahar Kechadi, Hung Q. Ngo:
Domain Adaptation in Nested Named Entity Recognition From Scientific Articles in Agriculture. SoICT 2023: 48-55 - [c28]Hoang Nguyen, Nam Le, Khang Tran, Ngoc Hoang Luong:
Simulated Annealing with Dynamic Programming-based Vertex Insertion for Efficiently Solving the Traveling Thief Problem. SoICT 2023: 165-172 - [c27]Thai Huy Nguyen, Ngoc Hoang Luong:
Understanding the Role of Population Experiences in Proximal Distilled Evolutionary Reinforcement Learning. SoICT 2023: 205-212 - [c26]Truong Do, Ngoc Hoang Luong:
Bias-free Trading Algorithms with Momentum Scores for the Vietnamese Stock Market. SoICT 2023: 701-706 - [c25]Vu Huynh, The Viet Le, Ngoc Hoang Luong:
Self-Adaptive Ant System with Hierarchical Clustering for the Thief Orienteering Problem. SoICT 2023: 723-730 - 2022
- [c24]Hieu Trung Nguyen, Khang Tran, Ngoc Hoang Luong:
Combining Soft-Actor Critic with Cross-Entropy Method for Policy Search in Continuous Control. CEC 2022: 1-8 - [c23]Quan Minh Phan, Ngoc Hoang Luong:
TF-MOPNAS: Training-free Multi-objective Pruning-Based Neural Architecture Search. ICCCI 2022: 297-310 - [c22]Long Doan, Hieu Le, Huy Dang, Long Tran, Dao Long, Hai Minh Nguyen, Hanh Pham, Nam Nguyen, Ngoc Hoang Luong, Huynh Thi Thanh Binh:
TF-GeneNAS: An evolution-based training-free approach to Neural Architecture Search. IJCNN 2022: 1-7 - [c21]An Vo, Tan Ngoc Pham, Van Bich Nguyen, Ngoc Hoang Luong:
Training-Free Multi-Objective and Many-Objective Evolutionary Neural Architecture Search with Synaptic Flow. SoICT 2022: 1-8 - [c20]Thai Bao Tran, Ngoc Hoang Luong:
Benchmarking Gradient Estimation Mechanisms in Evolution Strategies for Solving Black-Box Optimization Functions and Reinforcement Learning Problems. SoICT 2022: 39-46 - 2021
- [c19]Michal Witold Przewozniczek, Marcin M. Komarnicki, Peter A. N. Bosman, Dirk Thierens, Bartosz Frej, Ngoc Hoang Luong:
Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. GECCO Companion 2021: 1442-1450 - [c18]Tu Do, Ngoc Hoang Luong:
Training-Free Multi-objective Evolutionary Neural Architecture Search via Neural Tangent Kernel and Number of Linear Regions. ICONIP (2) 2021: 335-347 - [c17]Quan Minh Phan, Ngoc Hoang Luong:
Enhancing Multi-objective Evolutionary Neural Architecture Search with Surrogate Models and Potential Point-Guided Local Searches. IEA/AIE (1) 2021: 460-472 - [c16]Tu Do, Ngoc Hoang Luong:
Insightful and Practical Multi-objective Convolutional Neural Network Architecture Search with Evolutionary Algorithms. IEA/AIE (1) 2021: 473-479 - 2018
- [c15]Ngoc Hoang Luong, Tanja Alderliesten, Peter A. N. Bosman:
Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizations. GECCO 2018: 705-712 - [c14]G. H. Aalvanger, Ngoc Hoang Luong, Peter A. N. Bosman, Dirk Thierens:
Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem. PPSN (1) 2018: 146-157 - 2017
- [c13]Anton Bouter, Ngoc Hoang Luong, Cees Witteveen, Tanja Alderliesten, Peter A. N. Bosman:
The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 537-544 - [c12]Krzysztof L. Sadowski, Marjolein C. van der Meer, Ngoc Hoang Luong, Tanja Alderliesten, Dirk Thierens, Rob van der Laarse, Yury Niatsetski, Arjan Bel, Peter A. N. Bosman:
Exploring trade-offs between target coverage, healthy tissue sparing, and the placement of catheters in HDR brachytherapy for prostate cancer using a novel multi-objective model-based mixed-integer evolutionary algorithm. GECCO 2017: 1224-1231 - [c11]Ngoc Hoang Luong, Anton Bouter, Marjolein C. van der Meer, Yury Niatsetski, Cees Witteveen, Arjan Bel, Tanja Alderliesten, Peter A. N. Bosman:
Efficient, effective, and insightful tackling of the high-dose-rate brachytherapy treatment planning problem for prostate cancer using evolutionary multi-objective optimization algorithms. GECCO (Companion) 2017: 1372-1379 - 2016
- [c10]Peter A. N. Bosman, Ngoc Hoang Luong, Dirk Thierens:
Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms. GECCO 2016: 637-644 - 2015
- [c9]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning. GECCO 2015: 1231-1238 - 2014
- [c8]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Multi-objective gene-pool optimal mixing evolutionary algorithms. GECCO 2014: 357-364 - [c7]Ngoc Hoang Luong, Marinus O. W. Grond, Han La Poutré, Peter A. N. Bosman:
Efficiency enhancements for evolutionary capacity planning in distribution grids. GECCO (Companion) 2014: 1189-1196 - [c6]Marinus O. W. Grond, Ngoc Hoang Luong, Johan Morren, Peter A. N. Bosman, Han Slootweg, Han La Poutré:
Practice-oriented optimization of distribution network planning using metaheuristic algorithms. PSCC 2014: 1-8 - 2013
- [c5]Hoang N. Luong, Marinus O. W. Grond, Peter A. N. Bosman, Han La Poutré:
Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms. Artificial Evolution 2013: 93-105 - 2012
- [c4]Hoang N. Luong, Peter A. N. Bosman:
Elitist Archiving for Multi-Objective Evolutionary Algorithms: To Adapt or Not to Adapt. PPSN (2) 2012: 72-81 - 2010
- [c3]Hoang N. Luong, Hai T. T. Nguyen, Chang Wook Ahn:
Entropy-based substructural local search for the bayesian optimization algorithm. GECCO 2010: 335-342 - [c2]Hai T. T. Nguyen, Hoang N. Luong, Chang Wook Ahn:
Entropy measurement-based estimation model for bayesian optimization algorithm. GECCO 2010: 343-350 - [c1]Hoang Ngoc Luong, Hai Thanh Thi Nguyen, Chang Wook Ahn:
Entropy-Based Evaluation Relaxation Strategy for Bayesian Optimization Algorithm. IEA/AIE (2) 2010: 126-135
Informal and Other Publications
- 2024
- [i3]An Vo, Ngoc Hoang Luong:
Efficient Multi-Objective Neural Architecture Search via Pareto Dominance-based Novelty Search. CoRR abs/2407.20656 (2024) - 2023
- [i2]Minh Le, Nhan Nguyen, Ngoc Hoang Luong:
Efficacy of Neural Prediction-Based NAS for Zero-Shot NAS Paradigm. CoRR abs/2308.16775 (2023) - 2020
- [i1]Quoc Thai Nguyen, Thoai Linh Nguyen, Ngoc Hoang Luong, Quoc Hung Ngo:
Fine-Tuning BERT for Sentiment Analysis of Vietnamese Reviews. CoRR abs/2011.10426 (2020)
Coauthor Index
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