I am broadly interested in interactive machine learning and artificial curiosity & creativity. This includes aspects of online active learning, reinforcement learning, representation learning, with applications in information retrieval, human-robot interaction, and autonomous developmental robots.
H. Ngo, M. Luciw, A. Forster, J. Schmidhuber. Confidence-Based Progress-Driven Self-Generated Goals for Skill Acquisition in Developmental Robots. Frontiers in Cognitive Science Journal, Oct. 2013. (Open Access)
H. Ngo, M. Luciw, V. Ngo, J. Schmidhuber. Upper Confidence Weighted Learning for Efficient Exploration in Multiclass Prediction with Binary Feedback. IJCAI 2013, Beijing, China. (PDF). A longer version of the paper is under revision review for TiiS: ACM Trans. on Interactive Intelligent Systems.
H. Ngo, M. Luciw, A. Forster, J. Schmidhuber. Learning Skills from Play: Artificial Curiosity on a Katana Robot Arm. IJCNN 2012. (IM-CLeVeR project page, PDF)
H. Ngo, M. Ring, J. Schmidhuber. Compression Progress-based Curiosity Drive for Developmental Learning. ICDL-EpiRob 2011, Frankfurt, 2011. (PDF)
V. La, S.Y. Lee, H.X. Le, Hung Ngo, H. Kim, M. Han, Y.K. Lee. Semi Markov Conditional Random Fields for Accelerometer Based Activity Recognition. Journal of Applied Intelligence, Mar. 2010 (PDF).