4 papers
Optimizing Neurorobot Policy under Limited Demonstration Data through Preference Regret
Viet Dung Nguyen, Yuhang Song, Anh Nguyen +3
Robot reinforcement learning from demonstrations (RLfD) assumes that expert data is abundant; this is usually unrealistic in the real world given data scarcity as well as high coll…
Enhancing Eye Feature Estimation from Event Data Streams through Adaptive Inference State Space Modeling
Viet Dung Nguyen, Mobina Ghorbaninejad, Chengyi Ma +5
Eye feature extraction from event-based data streams can be performed efficiently and with low energy consumption, offering great utility to real-world eye tracking pipelines. Howe…
R-AIF: Solving Sparse-Reward Robotic Tasks from Pixels with Active Inference and World Models
Viet Dung Nguyen, Zhizhuo Yang, Christopher L. Buckley +1
Although research has produced promising results demonstrating the utility of active inference (AIF) in Markov decision processes (MDPs), there is relatively less work that builds…
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking Systems
Viet Dung Nguyen, Reynold Bailey, Gabriel J. Diaz +3
Eye image segmentation is a critical step in eye tracking that has great influence over the final gaze estimate. Segmentation models trained using supervised machine learning can e…