SCALES: From Fairness Principles to Constrained Decision-Making,
Sreejith Balakrishnan★, Jianxin Bi★, and Harold Soh★
, AAAI/ACM conference on Artificial Intelligence, Ethics and Society (AIES), 2022
MIRROR: Differentiable Deep Social Projection for Assistive Human-Robot Communication,
Kaiqi Chen★, Jeffrey Fong★, and Harold Soh★
, Robotics: Science and Systems (R:SS), 2022
When your boss is a robot: Workers are more spiteful to robot supervisors that seem more human,
Kai Chi Yam, E-Yang Goh, Ryan Fehr, Randy Lee, Harold Soh★, Kurt Gray
, Journal of Experimental Social Psychology
[BibTeX]
[BibTeX]
The Dynamics of Q-learning in Population Games: a Physics-Inspired Continuity Equation Model,
Shuyue Hu★, Chin-Wing Leung, Ho-fung Leung, and Harold Soh★
, International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022
Deep Explicit Duration Switching Models for Time Series,
Abdul Fatir Ansari★, Konstantinos Benidis, Richard Kurle, Ali Caner Turkmen, Harold Soh★, Alex Smola, Bernie Wang, Tim Januschowski
, Neural Information Processing Systems (NeurIPS), 2021
Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects,
Tasbolat Taunyazov★, Luar Shui Song★, Eugene Lim★, Hian Hian See, David Lee, Benjamin C.K. Tee, Harold Soh★
, IEEE International Conference on Intelligent Robots and Systems (IROS), 2021
Multi-Modal Mutual Information (MuMMI) Training for Robust Self-Supervised Deep Reinforcement Learning,
Kaiqi Chen★, Yong Lee★, and Harold Soh★
, IEEE International Conference on Robotics and Automation (ICRA), 2021
Embedding Symbolic Temporal Knowledge into Deep Sequential Models,
Yaqi Xie ★, Fan Zhou ★, and Harold Soh ★
, IEEE International Conference on Robotics and Automation (ICRA), 2021
The Evolutionary Dynamics of Independent Learning Agents in Population Games,
Shuyue Hu ★, Chin-Wing Leung, Ho-fung Leung, and Harold Soh ★
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[BibTeX]
Refining Deep Generative Models via Discriminator Gradient Flow,
Abdul Fatir Ansari ★, Ming Liang Ang ★, and Harold Soh ★
, International Conference on Learning Representations (ICLR), 2021
(28.6% Acceptance Rate)
A Theoretical Framework for Large-Scale Human-Robot Interaction with Groups of Learning Agents,
Nicholas Teh ★, Shuyue Hu ★, and Harold Soh ★
, Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2021
Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization,
Sreejith Balakrishnan ★, Quoc Phong Nguyen, Bryan Kian Hsiang Low, and Harold Soh ★
, Neural Information Processing Systems (NeurIPS), 2020
(20.1% Acceptance Rate)
Trust in Robots: Challenges and Opportunities,
Bing Cai Kok★, and Harold Soh ★
, Current Robotics Reports, 2020
Robots at work: People prefer—and forgive—service robots with perceived feelings,
Kai Chi Yam, Yochanan Bigman, Pok Man Tang, Remus Ilies, David De Cremer, Harold Soh ★, and Kurt Gray
, Journal of Applied Psychology, 2020
Getting to Know One Another: Calibrating Intent, Capabilities and Trust for Human-Robot Collaboration,
Joshua Lee★, Jeffrey Fong★, Bing Cai Kok★, and Harold Soh ★
, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
TactileSGNet: A Spiking Graph Neural Network for Event-based Tactile Object Recognition,
Fuqiang Gu★, Weicong Sng★, Tasbolat Taunyazov★, and Harold Soh ★
, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
Fast Texture Classification Using Tactile Neural Coding and Spiking Neural Network,
Tasbolat Taunyazov★, Yansong Chua, Ruihan Gao, Harold Soh ★, and Yan Wu
, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020
Event-Driven Visual-Tactile Sensing and Learning for Robots,
Tasbolat Taunyazov★, Weicong Sng★, Hian Hian See, Brian Lim, Jethro Kuan★, Abdul Fatir Ansari★, Benjamin Tee, and Harold Soh ★
, Robotics: Science and Systems Conference (RSS), 2020
A Characteristic Function Approach to Deep Implicit Generative Modeling,
Abdul Fatir Ansari★, Jonathan Scarlett, and Harold Soh★
, The Conference on Computer Vision and Pattern Recognition (CVPR), 2020
(22.1% Acceptance Rate, Oral Presentation ~5%)
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series,
Zhi-Xuan Tan, Harold Soh ★, Desmond Ong
, Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 2020
(20.6% Acceptance rate, Oral Presentation)
Multi-Task Trust Transfer for Human Robot Interaction,
Harold Soh ★, Yaqi Xie★, Min Chen, and David Hsu
, International Journal of Robotics Research (IJRR), 2020
(Impact Factor: 6.134)
Trust-Aware Decision Making for Human-Robot Collaboration: Model Learning and Planning,
Min Chen, Stefanos Nikolaidis, Harold Soh ★, David Hsu, and Siddhartha Srinivasa
, ACM Transactions on Human Robot Interaction (THRI), 2020
Modeling the Interplay of Trust and Attention in HRI: an Autonomous Vehicle Study,
Indu Prasad Bodala★, Bing Cai Kok★, Weicong Sng★, and Harold Soh ★
, Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2020
Juiced and Ready to Predict Private Information in Deep Cooperative Reinforcement Learning,
Eugene Lim★, Bing Cai Kok★, Joshua Lee★, Songli Wang★, and Harold Soh ★
, Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2020
Embedding Symbolic Knowledge into Deep Networks,
Yaqi Xie★, Ziwei Xu, Mohan Kankanhalli, Kuldeep S. Meel, and Harold Soh ★
, Neural Information Processing Systems (NeurIPS), 2019
(21% Acceptance rate)
Hyperprior Induced Unsupervised Disentanglement of Latent Representations,
Abdul Fatir Ansari★ and Harold Soh ★
, Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019
(16.2% Acceptance Rate)
Robot Capability and Intention in Trust-based Decisions across Tasks,
Xie Yaqi★, Indu Prasad★, Desmond Ong, David Hsu and Harold Soh ★
, ACM/IEEE Conference on Human Robot Interaction (HRI), 2019
(24% Acceptance Rate)
Towards Effective Tactile Identification of Textures using a Hybrid Touch Approach,
Tasbolat Taunyazov★, Hui Fang Koh, Yan Wu, Caixia Cai and Harold Soh ★
, IEEE International Conference on Robotics and Automation (ICRA), 2019
Applying Probabilistic Programming to Affective Computing,
Desmond Ong, Harold Soh ★, Jamil Zaki and Noah Goodman
, IEEE Transactions on Affective Computing, 2019
(Impact Factor: 6.288)
Deep Language-based Critiquing for Recommender Systems,
Ga Wu, Kai Luo, Scott Sanner and Harold Soh ★
, ACM Recommender Systems Conference (RecSys), 2019
(19% Acceptance Rate)
Trust Dynamics and Transfer across Human-Robot Interaction Tasks: Bayesian and Neural Computational Models,
Harold Soh ★, Shu Pan★, Min Chen and David Hsu
, IJCAI Best Paper Sister Track, 2019
The Transfer of Human Trust in Robot Capabilities across Tasks,
Harold Soh ★, Shu Pan★, Min Chen, and David Hsu
, Robotics Science and Systems (RSS), 2018
(Best Paper Award Finalist)
Generation Meets Recommendation: Proposing Novel Items for Groups of Users,
Vo Vinh Thanh★ and Harold Soh ★
, ACM Recommender Systems Conference (RecSys), 2018
(17.7% Acceptance Rate, Best Long Paper Award Runner-up)
Planning with Trust for Human Robot Collaboration,
Min Chen, Stefanos Nikolaidis, Harold Soh ★, David Hsu, and Siddhartha Srinivasa
, ACM/IEEE Conference on Human Robot Interaction (HRI), 2018
(23% Acceptance Rate, Best Paper Award Finalist)
Human Trust in Robot Capabilities across Tasks,
Pan Shu★, Min Chen, Stefanos Nikolaidis, David Hsu, and Harold Soh ★
, Late Breaking Report, ACM/IEEE Conference on Human Robot Interaction (HRI), 2018
Z-Transforms and its Inference on Partially Observable Point Processes,
Young Lee★, Vo Vinh Thanh★, Kar Wai Lim, and Harold Soh ★
, Intl. Joint Conference on Artificial Intelligence (IJCAI), 2018
(20.5% Acceptance Rate)
Collaborative Filtering with Behavioral Models,
Dusan Sovilj, Scott Sanner, Harold Soh ★, and Hanze Li
, ACM User Modeling and Personalization Conference (UMAP), 2018
(28% Acceptance Rate)
Measuring and Mitigating the Costs of Attentional Switches in Active Network Monitoring for Cybersecurity,
Sean W. Kortschot, Dusan Sovilj, Greg A. Jamieson, Scott Sanner, Chelsea Carrasco, and Harold Soh★
, Human Factors: The Journal of the Human Factors and Ergonomics Society