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2020 – today
- 2024
[j10]Xudong Shen, Hannah Brown, Jiashu Tao
, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez:
Directions of Technical Innovation for Regulatable AI Systems. Commun. ACM 67(11): 82-89 (2024)- [j9]Zeyu Feng, Hao Luan, Pranav Goyal, Harold Soh:
LTLDoG: Satisfying Temporally-Extended Symbolic Constraints for Safe Diffusion-Based Planning. IEEE Robotics Autom. Lett. 9(10): 8571-8578 (2024) - [c57]Jiaming Wang, Harold Soh:
Probable Object Location (POLo) Score Estimation for Efficient Object Goal Navigation. ICRA 2024: 5221-5227 - [c56]Alvin Heng, Abdul Fatir Ansari, Harold Soh:
Generative Modeling with Flow-Guided Density Ratio Learning. ECML/PKDD (2) 2024: 250-267 - [e2]Dan Grollman, Elizabeth Broadbent, Wendy Ju, Harold Soh, Tom Williams:
Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024, Boulder, CO, USA, March 11-15, 2024. ACM 2024 [contents] - [e1]Dan Grollman, Elizabeth Broadbent, Wendy Ju, Harold Soh, Tom Williams:
Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2024, Boulder, CO, USA, March 11-15, 2024. ACM 2024 [contents] - [i45]Kaiqi Chen, Eugene Lim, Kelvin Lin, Yiyang Chen, Harold Soh:
Behavioral Refinement via Interpolant-based Policy Diffusion. CoRR abs/2402.16075 (2024) - [i44]Bowen Zhang, Harold Soh:
Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction. CoRR abs/2404.03868 (2024) - [i43]Samson Yu, Kelvin Lin, Anxing Xiao, Jiafei Duan, Harold Soh:
Octopi: Object Property Reasoning with Large Tactile-Language Models. CoRR abs/2405.02794 (2024) - [i42]Zeyu Feng, Hao Luan, Pranav Goyal, Harold Soh:
LTLDoG: Satisfying Temporally-Extended Symbolic Constraints for Safe Diffusion-based Planning. CoRR abs/2405.04235 (2024) - [i41]Alvin Heng, Alexandre H. Thiery, Harold Soh:
Out-of-Distribution Detection with a Single Unconditional Diffusion Model. CoRR abs/2405.11881 (2024) - [i40]Linh Kästner, Volodymyir Shcherbyna, Huajian Zeng, Tuan Anh Le, Maximilian Ho-Kyoung Schreff, Halid Osmaev, Nam Truong Tran, Diego Diaz, Jan Golebiowski, Harold Soh, Jens Lambrecht:
Arena 3.0: Advancing Social Navigation in Collaborative and Highly Dynamic Environments. CoRR abs/2406.00837 (2024) - [i39]Ce Hao, Kelvin Lin, Siyuan Luo, Harold Soh:
Language-Guided Manipulation with Diffusion Policies and Constrained Inpainting. CoRR abs/2406.09767 (2024) - [i38]Volodymyr Shcherbyna, Linh Kästner, Diego Diaz, Huu Giang Nguyen, Maximilian Ho-Kyoung Schreff, Tim Lenz, Jonas Kreutz, Ahmed Martban, Huajian Zeng, Harold Soh:
Arena 4.0: A Comprehensive ROS2 Development and Benchmarking Platform for Human-centric Navigation Using Generative-Model-based Environment Generation. CoRR abs/2409.12471 (2024) - [i37]Zeyu Feng, Hao Luan, Kevin Yuchen Ma, Harold Soh:
Diffusion Meets Options: Hierarchical Generative Skill Composition for Temporally-Extended Tasks. CoRR abs/2410.02389 (2024) - 2023
- [c55]Abdul Fatir Ansari, Alvin Heng, Andre Lim, Harold Soh:
Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series. ICML 2023: 926-951 - [c54]Zeyu Feng, Bowen Zhang, Jianxin Bi, Harold Soh:
Safety-Constrained Policy Transfer with Successor Features. ICRA 2023: 7219-7225 - [c53]Tasbolat Taunyazov, Heng Zhang, John Patrick Eala, Na Zhao, Harold Soh:
Refining 6-DoF Grasps with Context-Specific Classifiers. IROS 2023: 6861-6867 - [c52]Bowen Zhang, Harold Soh:
Large Language Models as Zero-Shot Human Models for Human-Robot Interaction. IROS 2023: 7961-7968 - [c51]Kaiqi Chen, Jing Yu Lim, Kingsley Kuan, Harold Soh:
Latent Emission-Augmented Perspective-Taking (LEAPT) for Human-Robot Interaction. IROS 2023: 8006-8013 - [c50]Alvin Heng, Harold Soh:
Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models. NeurIPS 2023 - [c49]Shuyue Hu, Harold Soh, Georgios Piliouras:
The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium. NeurIPS 2023 - [i36]Shuyue Hu, Harold Soh, Georgios Piliouras:
Heterogeneous Beliefs and Multi-Population Learning in Network Games. CoRR abs/2301.04929 (2023) - [i35]Abdul Fatir Ansari, Alvin Heng, Andre Lim, Harold Soh:
Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series. CoRR abs/2301.11308 (2023) - [i34]Yaqi Xie, Chen Yu, Tongyao Zhu, Jinbin Bai, Ze Gong, Harold Soh:
Translating Natural Language to Planning Goals with Large-Language Models. CoRR abs/2302.05128 (2023) - [i33]Bowen Zhang, Harold Soh:
Large Language Models as Zero-Shot Human Models for Human-Robot Interaction. CoRR abs/2303.03548 (2023) - [i32]Alvin Heng, Abdul Fatir Ansari, Harold Soh:
Generative Modeling with Flow-Guided Density Ratio Learning. CoRR abs/2303.03714 (2023) - [i31]Alvin Heng, Harold Soh:
Selective Amnesia: A Continual Learning Approach to Forgetting in Deep Generative Models. CoRR abs/2305.10120 (2023) - [i30]Xudong Shen, Hannah Brown, Jiashu Tao, Martin Strobel, Yao Tong, Akshay Narayan, Harold Soh, Finale Doshi-Velez:
Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities. CoRR abs/2306.12609 (2023) - [i29]Kaiqi Chen, Jing Yu Lim, Kingsley Kuan, Harold Soh:
Latent Emission-Augmented Perspective-Taking (LEAPT) for Human-Robot Interaction. CoRR abs/2308.06498 (2023) - [i28]Tasbolat Taunyazov, Heng Zhang, John Patrick Eala, Na Zhao, Harold Soh:
Refining 6-DoF Grasps with Context-Specific Classifiers. CoRR abs/2308.06928 (2023) - [i27]Tasbolat Taunyazov, Kelvin Lin, Harold Soh:
GRaCE: Optimizing Grasps to Satisfy Ranked Criteria in Complex Scenarios. CoRR abs/2309.08887 (2023) - [i26]Jiaming Wang, Harold Soh:
Probable Object Location (POLo) Score Estimation for Efficient Object Goal Navigation. CoRR abs/2311.07992 (2023) - 2022
- [c48]Sreejith Balakrishnan, Jianxin Bi, Harold Soh:
SCALES: From Fairness Principles to Constrained Decision-Making. AIES 2022: 46-55 - [c47]Shuyue Hu, Chin-Wing Leung, Ho-fung Leung, Harold Soh:
The Dynamics of Q-learning in Population Games: A Physics-inspired Continuity Equation Model. AAMAS 2022: 615-623 - [c46]Cynthia Matuszek, Harold Soh, Matthew C. Gombolay, Nakul Gopalan, Reid G. Simmons, Stefanos Nikolaidis:
Machine Learning in Human-Robot Collaboration: Bridging the Gap. HRI 2022: 1275-1277 - [c45]Kaiqi Chen, Jeffrey Fong, Harold Soh:
MIRROR: Differentiable Deep Social Projection for Assistive Human-Robot Communication. Robotics: Science and Systems 2022 - [i25]Shuyue Hu, Chin-Wing Leung, Ho-fung Leung, Harold Soh:
The Dynamics of Q-learning in Population Games: a Physics-Inspired Continuity Equation Model. CoRR abs/2203.01500 (2022) - [i24]Kaiqi Chen, Jeffrey Fong, Harold Soh:
MIRROR: Differentiable Deep Social Projection for Assistive Human-Robot Communication. CoRR abs/2203.02877 (2022) - [i23]Sreejith Balakrishnan, Jianxin Bi, Harold Soh:
SCALES: From Fairness Principles to Constrained Decision-Making. CoRR abs/2209.10860 (2022) - [i22]Eugene Lim, Harold Soh:
Observed Adversaries in Deep Reinforcement Learning. CoRR abs/2210.06787 (2022) - [i21]Zeyu Feng, Bowen Zhang, Jianxin Bi, Harold Soh:
Safety-Constrained Policy Transfer with Successor Features. CoRR abs/2211.05361 (2022) - 2021
- [j8]Desmond C. Ong, Harold Soh, Jamil Zaki, Noah D. Goodman:
Applying Probabilistic Programming to Affective Computing. IEEE Trans. Affect. Comput. 12(2): 306-317 (2021) - [c44]Nicholas Teh, Shuyue Hu, Harold Soh:
A Theoretical Framework for Large-Scale Human-Robot Interaction with Groups of Learning Agents. HRI (Companion) 2021: 489-493 - [c43]Abdul Fatir Ansari, Ming Liang Ang, Harold Soh:
Refining Deep Generative Models via Discriminator Gradient Flow. ICLR 2021 - [c42]Yaqi Xie, Fan Zhou, Harold Soh:
Embedding Symbolic Temporal Knowledge into Deep Sequential Models. ICRA 2021: 4267-4273 - [c41]Kaiqi Chen, Yong Lee, Harold Soh:
Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning. ICRA 2021: 4274-4280 - [c40]Tasbolat Taunyazov, Luar Shui Song, Eugene Lim, Hian-Hian See, David Lee, Benjamin C. K. Tee, Harold Soh:
Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects. IROS 2021: 1755-1762 - [c39]Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski:
Deep Explicit Duration Switching Models for Time Series. NeurIPS 2021: 29949-29961 - [i20]Yaqi Xie, Fan Zhou, Harold Soh:
Embedding Symbolic Temporal Knowledge into Deep Sequential Models. CoRR abs/2101.11981 (2021) - [i19]Tasbolat Taunyazov, Luar Shui Song, Eugene Lim, Hian-Hian See, David Lee, Benjamin C. K. Tee, Harold Soh:
Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects. CoRR abs/2106.00489 (2021) - [i18]Kaiqi Chen, Yong Lee, Harold Soh:
Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning. CoRR abs/2107.02339 (2021) - [i17]Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski:
Deep Explicit Duration Switching Models for Time Series. CoRR abs/2110.13878 (2021) - 2020
- [j7]Harold Soh, Yaqi Xie, Min Chen, David Hsu:
Multi-task trust transfer for human-robot interaction. Int. J. Robotics Res. 39(2-3) (2020) - [j6]Min Chen, Stefanos Nikolaidis, Harold Soh, David Hsu, Siddhartha S. Srinivasa:
Trust-Aware Decision Making for Human-Robot Collaboration: Model Learning and Planning. ACM Trans. Hum. Robot Interact. 9(2): 9:1-9:23 (2020) - [c38]Zhi-Xuan Tan, Harold Soh, Desmond C. Ong:
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series. AAAI 2020: 10334-10341 - [c37]Abdul Fatir Ansari, Jonathan Scarlett, Harold Soh:
A Characteristic Function Approach to Deep Implicit Generative Modeling. CVPR 2020: 7476-7484 - [c36]Indu P. Bodala, Bing Cai Kok, Weicong Sng, Harold Soh:
Modeling the Interplay of Trust and Attention in HRI: An Autonomous Vehicle Study. HRI (Companion) 2020: 145-147 - [c35]Eugene Lim, Bing Cai Kok, Songli Wang, Joshua Lee, Harold Soh:
Juiced and Ready to Predict Private Information in Deep Cooperative Reinforcement Learning. HRI (Companion) 2020: 343-345 - [c34]Joshua Lee, Jeffrey Fong, Bing Cai Kok, Harold Soh:
Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration. IROS 2020: 6296-6303 - [c33]Fuqiang Gu, Weicong Sng, Tasbolat Taunyazov, Harold Soh:
TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition. IROS 2020: 9876-9882 - [c32]Tasbolat Taunyazov, Yansong Chua, Ruihan Gao, Harold Soh, Yan Wu:
Fast Texture Classification Using Tactile Neural Coding and Spiking Neural Network. IROS 2020: 9890-9895 - [c31]Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh:
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. NeurIPS 2020 - [c30]Tasbolat Taunyazov, Weicong Sng, Brian Lim, Hian-Hian See, Jethro Kuan, Abdul Fatir Ansari, Benjamin C. K. Tee, Harold Soh:
Event-Driven Visual-Tactile Sensing and Learning for Robots. Robotics: Science and Systems 2020 - [i16]Hian-Hian See, Brian Lim, Si Li, Haicheng Yao, Wen Cheng, Harold Soh, Benjamin C. K. Tee:
ST-MNIST - The Spiking Tactile MNIST Neuromorphic Dataset. CoRR abs/2005.04319 (2020) - [i15]Shuyue Hu, Chin-Wing Leung, Ho-fung Leung, Harold Soh:
The Evolutionary Dynamics of Independent Learning Agents in Population Games. CoRR abs/2006.16068 (2020) - [i14]Joshua Lee, Jeffrey Fong, Bing Cai Kok, Harold Soh:
Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration. CoRR abs/2008.00699 (2020) - [i13]Fuqiang Gu, Weicong Sng, Tasbolat Taunyazov, Harold Soh:
TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition. CoRR abs/2008.08046 (2020) - [i12]Tasbolat Taunyazov, Weicong Sng, Hian-Hian See, Brian Lim, Jethro Kuan, Abdul Fatir Ansari, Benjamin C. K. Tee, Harold Soh:
Event-Driven Visual-Tactile Sensing and Learning for Robots. CoRR abs/2009.07083 (2020) - [i11]Sreejith Balakrishnan, Quoc Phong Nguyen, Bryan Kian Hsiang Low, Harold Soh:
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization. CoRR abs/2011.08541 (2020) - [i10]Abdul Fatir Ansari, Ming Liang Ang, Harold Soh:
Refining Deep Generative Models via Wasserstein Gradient Flows. CoRR abs/2012.00780 (2020)
2010 – 2019
- 2019
- [c29]Abdul Fatir Ansari, Harold Soh:
Hyperprior Induced Unsupervised Disentanglement of Latent Representations. AAAI 2019: 3175-3182 - [c28]Yaqi Xie, Indu P. Bodala, Desmond C. Ong, David Hsu, Harold Soh:
Robot Capability and Intention in Trust-Based Decisions Across Tasks. HRI 2019: 39-47 - [c27]Tasbolat Taunyazov, Hui Fang Koh, Yan Wu, Caixia Cai, Harold Soh:
Towards Effective Tactile Identification of Textures using a Hybrid Touch Approach. ICRA 2019: 4269-4275 - [c26]Harold Soh, Pan Shu, Min Chen, David Hsu:
Trust Dynamics and Transfer across Human-Robot Interaction Tasks: Bayesian and Neural Computational Models. IJCAI 2019: 6226-6230 - [c25]Yaqi Xie, Ziwei Xu, Kuldeep S. Meel, Mohan S. Kankanhalli, Harold Soh:
Embedding Symbolic Knowledge into Deep Networks. NeurIPS 2019: 4235-4245 - [c24]Ga Wu, Kai Luo, Scott Sanner, Harold Soh:
Deep language-based critiquing for recommender systems. RecSys 2019: 137-145 - [i9]Desmond C. Ong, Harold Soh, Jamil Zaki, Noah D. Goodman:
Applying Probabilistic Programming to Affective Computing. CoRR abs/1903.06445 (2019) - [i8]Zhi-Xuan Tan, Harold Soh, Desmond C. Ong:
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series. CoRR abs/1905.13570 (2019) - [i7]Yaqi Xie, Ziwei Xu, Kuldeep S. Meel, Mohan S. Kankanhalli, Harold Soh:
Semantically-Regularized Logic Graph Embeddings. CoRR abs/1909.01161 (2019) - [i6]Yaqi Xie, Indu P. Bodala, Desmond C. Ong, David Hsu, Harold Soh:
Robot Capability and Intention in Trust-based Decisions across Tasks. CoRR abs/1909.05329 (2019) - [i5]Abdul Fatir Ansari, Jonathan Scarlett, Harold Soh:
A Characteristic Function Approach to Deep Implicit Generative Modeling. CoRR abs/1909.07425 (2019) - 2018
- [j5]Sean W. Kortschot, Dusan Sovilj, Greg A. Jamieson, Scott Sanner, Chelsea Carrasco, Harold Soh:
Measuring and Mitigating the Costs of Attentional Switches in Active Network Monitoring for Cybersecurity. Hum. Factors 60(7): 962-977 (2018) - [c23]Pan Shu, Min Chen, Indu P. Bodala, Stefanos Nikolaidis, David Hsu, Harold Soh:
Human Trust in Robot Capabilities across Tasks. HRI (Companion) 2018: 241-242 - [c22]Min Chen, Stefanos Nikolaidis, Harold Soh, David Hsu, Siddhartha S. Srinivasa:
Planning with Trust for Human-Robot Collaboration. HRI 2018: 307-315 - [c21]Young Lee, Thanh Vinh Vo, Kar Wai Lim, Harold Soh:
Z-Transforms and its Inference on Partially Observable Point Processes. IJCAI 2018: 2369-2375 - [c20]Thanh Vinh Vo, Harold Soh:
Generation meets recommendation: proposing novel items for groups of users. RecSys 2018: 145-153 - [c19]Harold Soh, Pan Shu, Min Chen, David Hsu:
The Transfer of Human Trust in Robot Capabilities across Tasks. Robotics: Science and Systems 2018 - [c18]Dusan Sovilj, Scott Sanner, Harold Soh, Hanze Li:
Collaborative Filtering with Behavioral Models. UMAP 2018: 91-99 - [i4]Min Chen, Stefanos Nikolaidis, Harold Soh, David Hsu, Siddhartha S. Srinivasa:
Planning with Trust for Human-Robot Collaboration. CoRR abs/1801.04099 (2018) - [i3]Harold Soh, Pan Shu, Min Chen, David Hsu:
The Transfer of Human Trust in Robot Capabilities across Tasks. CoRR abs/1807.01866 (2018) - [i2]Thanh Vinh Vo, Harold Soh:
Generation Meets Recommendation: Proposing Novel Items for Groups of Users. CoRR abs/1808.01199 (2018) - [i1]Abdul Fatir Ansari, Harold Soh:
Hyperprior Induced Unsupervised Disentanglement of Latent Representations. CoRR abs/1809.04497 (2018) - 2017
- [c17]Shamin Kinathil, Harold Soh, Scott Sanner:
Nonlinear Optimization and Symbolic Dynamic Programming for Parameterized Hybrid Markov Decision Processes. AAAI Workshops 2017 - [c16]Shamin Kinathil, Harold Soh, Scott Sanner:
Analytic Decision Analysis via Symbolic Dynamic Programming for Parameterized Hybrid MDPs. ICAPS 2017: 181-185 - [c15]Harold Soh, Scott Sanner, Madeleine White, Greg A. Jamieson:
Deep Sequential Recommendation for Personalized Adaptive User Interfaces. IUI 2017: 589-593 - [c14]Sean W. Kortschot, Dusan Sovilj, Harold Soh, Greg A. Jamieson, Scott Sanner, Chelsea Carrasco, Scott Ralph, Scott Langevin:
An open source adaptive user interface for network monitoring. SMC 2017: 1535-1539 - 2016
- [c13]Harold Soh:
Distance-Preserving Probabilistic Embeddings with Side Information: Variational Bayesian Multidimensional Scaling Gaussian Process. IJCAI 2016: 2011-2017 - 2015
- [j4]Harold Soh, Yiannis Demiris:
Learning assistance by demonstration: smart mobility with shared control and paired haptic controllers. J. Hum. Robot Interact. 4(3): 76-100 (2015) - [j3]Harold Soh, Yiannis Demiris:
Spatio-Temporal Learning With the Online Finite and Infinite Echo-State Gaussian Processes. IEEE Trans. Neural Networks Learn. Syst. 26(3): 522-536 (2015) - 2014
- [j2]Harold Soh, Yiannis Demiris:
Incrementally Learning Objects by Touch: Online Discriminative and Generative Models for Tactile-Based Recognition. IEEE Trans. Haptics 7(4): 512-525 (2014) - 2013
- [c12]Yanyu Su, Yan Wu, Harold Soh, Zhijiang Du, Yiannis Demiris:
Enhanced kinematic model for dexterous manipulation with an underactuated hand. IROS 2013: 2493-2499 - [c11]Harold Soh, Yiannis Demiris:
When and how to help: An iterative probabilistic model for learning assistance by demonstration. IROS 2013: 3230-3236 - [c10]Miguel Sarabia, Tuan Le Mau, Harold Soh, Shuto Naruse, Crispian Poon, Zhitian Liao, Kuen Cherng Tan, Zi Jian Lai, Yiannis Demiris:
iCharibot: Design and Field Trials of a Fundraising Robot. ICSR 2013: 412-421 - 2012
- [c9]Harold Soh, Yiannis Demiris:
Iterative temporal learning and prediction with the sparse online echo state gaussian process. IJCNN 2012: 1-8 - [c8]Harold Soh, Yanyu Su, Yiannis Demiris:
Online spatio-temporal Gaussian process experts with application to tactile classification. IROS 2012: 4489-4496 - 2011
- [c7]Harold Soh, Yiannis Demiris:
Multi-reward policies for medical applications: anthrax attacks and smart wheelchairs. GECCO (Companion) 2011: 471-478 - [c6]Harold Soh, Yiannis Demiris:
Evolving policies for multi-reward partially observable markov decision processes (MR-POMDPs). GECCO 2011: 713-720 - 2010
- [j1]Harold Soh, Yew-Soon Ong, Quoc Chinh Nguyen, Quang Huy Nguyen, Mohamed Salahuddin Habibullah, Terence Hung, Jer-Lai Kuo:
Discovering Unique, Low-Energy Pure Water Isomers: Memetic Exploration, Optimization, and Landscape Analysis. IEEE Trans. Evol. Comput. 14(3): 419-437 (2010)
2000 – 2009
- 2008
- [c5]Yan Wu, Gary Kee Khoon Lee, Xiuju Fu, Harold Soh, Terence Hung:
Mining Weather Information in Dengue Outbreak: Predicting Future Cases Based on Wavelet, SVM and GA. World Congress on Engineering (Selected Papers) 2008: 483-494 - 2007
- [c4]Mohamed Salahuddin, Terence Hung, Harold Soh, Endang Sulaiman, Yew-Soon Ong, Bu-Sung Lee, Ren Yunxia:
Grid-based PSE for Engineering of Materials (GPEM). CCGRID 2007: 309-316 - [c3]Xiuju Fu, Christina Liew, Harold Soh, Gary Kee Khoon Lee, Terence Hung, Lee-Ching Ng:
Time-series infectious disease data analysis using SVM and genetic algorithm. IEEE Congress on Evolutionary Computation 2007: 1276-1280 - [c2]Harold Soh, Yew-Soon Ong, Mohamed Salahuddin, Terence Hung, Bu-Sung Lee:
Playing in the Objective Space: Coupled Approximators for Multi-Objective Optimization. MCDM 2007: 325-332 - 2006
- [c1]Harold Soh, Michael Kirley:
moPGA: Towards a New Generation of Multi-objective Genetic Algorithms. IEEE Congress on Evolutionary Computation 2006: 1702-1709
Coauthor Index
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