Chong Jin Ong

Masood Dehghan, Chong Jin Ong: Discrete-time switching linear system with constraints: Characterization and computation of invariant sets under dwell-time consideration. Automatica 48(5): 964-969 (2012)

Masood Dehghan, Chong Jin Ong: Characterization and computation of disturbance invariant sets for constrained switched linear systems with dwell time restriction. Automatica 48(9): 2175-2181 (2012)

Dan Zhang, Li Yu, Qing-Guo Wang, Chong Jin Ong: Estimator Design for Discrete-Time Switched Neural Networks With Asynchronous Switching and Time-Varying Delay. IEEE Trans. Neural Netw. Learning Syst. 23(5): 827-834 (2012)

Jian-Bo Yang, Chong Jin Ong: An Effective Feature Selection Method via Mutual Information Estimation. IEEE Transactions on Systems, Man, and Cybernetics, Part B 42(6): 1550-1559 (2012)

Chong Jin Ong: Model Predictive Control with reduced number of variables for linear systems with bounded disturbances. CDC 2012: 3258-3263

Elmer G. Gilbert, Chong Jin Ong: Constrained linear systems with hard constraints and disturbances: An extended command governor with large domain of attraction. Automatica 47(2): 334-340 (2011)

Jian-Bo Yang, Chong Jin Ong: Determination of Global Minima of Some Common Validation Functions in Support Vector Machine. IEEE Transactions on Neural Networks 22(4): 654-659 (2011)

Jian-Bo Yang, Chong Jin Ong: Feature Selection Using Probabilistic Prediction of Support Vector Regression. IEEE Transactions on Neural Networks 22(6): 954-962 (2011)

Masood Dehghan, Chong Jin Ong, Peter C. Y. Chen: Characterization and computation of robust invariant sets for switching systems under dwell-time consideration. CDC-ECE 2011: 1166-1171

Masood Dehghan, Chong Jin Ong, Peter C. Y. Chen: Discrete-time switched linear system with constraints: Characterization and computation of invariant sets under dwell-time consideration. CDC-ECE 2011: 5473-5478

Chen Wang, Chong Jin Ong: Distributed model predictive control of dynamically decoupled systems with coupled cost. Automatica 46(12): 2053-2058 (2010)

Chen Wang, Chong Jin Ong, Melvyn Sim: Model Predictive Control Using Segregated Disturbance Feedback. IEEE Trans. Automat. Contr. 55(4): 831-840 (2010)

Chong Jin Ong, Shiyun Shao, Jianbo Yang: An improved algorithm for the solution of the regularization path of support vector machine. IEEE Transactions on Neural Networks 21(3): 451-462 (2010)

Shengfeng Zhou, Peter C. Y. Chen, Zhe Lu, Joo Hoo Nam, Hong Luo, Ruowen Ge, Chong Jin Ong, Wei Lin: Speed optimization for micropipette motion during zebrafish embryo microinjection. ICARCV 2010: 364-369

Jian-Bo Yang, Chong Jin Ong: Feature selection for support vector regression using probabilistic prediction. KDD 2010: 343-352

Chen Wang, Chong Jin Ong, Melvyn Sim: Convergence properties of constrained linear system under MPC control law using affine disturbance feedback. Automatica 45(7): 1715-1720 (2009)

Dan Sui, Le Feng, Morten Hovd, Chong Jin Ong: Decomposition principle in model predictive control for linear systems with bounded disturbances. Automatica 45(8): 1917-1922 (2009)

Shiyun Shao, Kai Quan Shen, Chong Jin Ong, Einar P. V. Wilder-Smith, Xiao Ping Li: Automatic EEG Artifact Removal: A Weighted Support Vector Machine Approach With Error Correction. IEEE Trans. Biomed. Engineering 56(2): 336-344 (2009)

Jian-Bo Yang, Kai Quan Shen, Chong Jin Ong, Xiao Ping Li: Feature Selection for MLP Neural Network: The Use of Random Permutation of Probabilistic Outputs. IEEE Transactions on Neural Networks 20(12): 1911-1922 (2009)

Chen Wang, Chong Jin Ong, Melvyn Sim: Linear systems with chance constraints: Constraint-admissible set and applications in predictive control. CDC 2009: 2875-2880

Chen Wang, Chong Jin Ong, Melvyn Sim: Distributed model predictive control of dynamically decoupled linear systems with coupled cost. CDC 2009: 5420-5425

Elmer G. Gilbert, Chong Jin Ong: An extended command governor for constrained linear systems with disturbances. CDC 2009: 6929-6934

Chen Wang, Chong Jin Ong, Melvyn Sim: Constrained linear system with disturbance: Convergence under disturbance feedback. Automatica 44(10): 2583-2587 (2008)

Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar P. V. Wilder-Smith: Feature selection via sensitivity analysis of SVM probabilistic outputs. Machine Learning 70(1): 1-20 (2008)

Chen Wang, Chong Jin Ong, Melvyn Sim: Constrained linear system under disturbance feedback: Convergence with probability one. CDC 2008: 2820-2825

Jian-Bo Yang, Kai Quan Shen, Chong Jin Ong, Xiao Ping Li: Feature selection via sensitivity analysis of MLP probabilistic outputs. SMC 2008: 774-779

Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar P. V. Wilder-Smith: Novel multi-class feature selection methods using sensitivity analysis of posterior probabilities. SMC 2008: 1116-1121

Shiyun Shao, Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Einar P. V. Wilder-Smith: Automatic identification and removal of artifacts in EEG using a probabilistic multi-class SVM approach with error correction. SMC 2008: 1134-1139

Masood Dehghan, Chong Jin Ong, Peter C. Y. Chen: Anti-windup design using auxiliary input for constrained linear systems. SMC 2008: 3226-3231

Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Hui Zheng, Einar P. V. Wilder-Smith: A Feature Selection Method for Multilevel Mental Fatigue EEG Classification. IEEE Trans. Biomed. Engineering 54(7): 1231-1237 (2007)

Chong Jin Ong, Dan Sui, Elmer G. Gilbert: Enlarging the terminal region of nonlinear model predictive control using the support vector machine method. Automatica 42(6): 1011-1016 (2006)

Chong Jin Ong, Elmer G. Gilbert: The minimal disturbance invariant set: Outer approximations via its partial sums. Automatica 42(9): 1563-1568 (2006)

L. J. Cao, S. Sathiya Keerthi, Chong Jin Ong, P. Uvaraj, Xiu Ju Fu, H. P. Lee: Developing parallel sequential minimal optimization for fast training support vector machine. Neurocomputing 70(1-3): 93-104 (2006)

L. J. Cao, S. Sathiya Keerthi, Chong Jin Ong, J. Q. Zhang, U. Periyathamby, Xiu Ju Fu, H. P. Lee: Parallel sequential minimal optimization for the training of support vector machines. IEEE Transactions on Neural Networks 17(4): 1039-1049 (2006)

Chee-Kong Chui, Swee-Hin Teoh, Chong Jin Ong, James H. Anderson, Ichiro Sakuma: Integrative Modeling of Liver Organ for Simulation of Flexible Needle Insertion. ICARCV 2006: 1-6

Dan Sui, Chong Jin Ong: Outer Approximation of the Minimal Disturbance Invariant Set of PWL Systems with Bounded Disturbances. ICARCV 2006: 1-5

Kai Quan Shen, Chong Jin Ong, Xiao Ping Li, Hui Zheng, Einar P. V. Wilder-Smith: Feature Selection Using SVM Probabilistic Outputs. ICONIP (1) 2006: 782-791

Wei Chu, Chong Jin Ong, S. Sathiya Keerthi: An improved conjugate gradient scheme to the solution of least squares SVM. IEEE Transactions on Neural Networks 16(2): 498-501 (2005)

Chong Jin Ong, S. Sathiya Keerthi, Elmer G. Gilbert, Z. H. Zhang: Stability regions for constrained nonlinear systems and their functional characterization via support-vector-machine learning. Automatica 40(11): 1955-1964 (2004)

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong: Bayesian support vector regression using a unified loss function. IEEE Transactions on Neural Networks 15(1): 29-44 (2004)

Martin M. S. Lee, S. Sathiya Keerthi, Chong Jin Ong, Dennis DeCoste: An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels. IEEE Transactions on Neural Networks 15(3): 750-757 (2004)

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong: Bayesian Trigonometric Support Vector Classifier. Neural Computation 15(9): 2227-225 (2003)

Min Shi, David S. Edwin, Rakesh Menon, Lixiang Shen, Jonathan Y. K. Lim, Han Tong Loh, S. Sathiya Keerthi, Chong Jin Ong: A Machine Learning Approach for the Curation of Biomedical Literature. ECIR 2003: 597-604

S. Sathiya Keerthi, Chong Jin Ong, Keng Boon Siah, David B. L. Lim, Wei Chu, Min Shi, David S. Edwin, Rakesh Menon, Lixiang Shen, Jonathan Y. K. Lim, Han Tong Loh: A Machine Learning Approach for the Curation of Biomedical Literature - KDD Cup 2002 (Task 1). SIGKDD Explorations 4(2): 93-94 (2002)

Chong Jin Ong, Elmer G. Gilbert: Fast versions of the Gilbert-Johnson-Keerthi distance algorithm: additional results and comparisons. IEEE Transactions on Robotics 17(4): 531-539 (2001)

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong: A Unified Loss Function in Bayesian Framework for Support Vector Regression. ICML 2001: 51-58

Chong Jin Ong, Eugene Huang, Sun-Mog Hong: A fast growth distance algorithm for incremental motions. IEEE Transactions on Robotics 16(6): 880-890 (2000)

S. Sathiya Keerthi, Chong Jin Ong, Eugene Huang, Elmer G. Gilbert: EquiDistance Diagram: A New Roadmap Method for Path Planning. ICRA 1999: 682-687

Chong Jin Ong, Elmer G. Gilbert: Robot path planning with penetration growth distance. J. Field Robotics 15(2): 57-74 (1998)

Chong Jin Ong, Eugene Huang: An Incremental Version of Growth Distance. ICRA 1998: 3671-3677

Chong Jin Ong: On the Quantification of Penetration between General Objects. I. J. Robotic Res. 16(3): 400-409 (1997)

Chong Jin Ong, Elmer G. Gilbert: The Gilbert-Johnson-Keerthi distance algorithm: a fast version for incremental motions. ICRA 1997: 1183-1189

Chong Jin Ong: Computation of penetration between smooth convex objects in three-dimensional space. J. Field Robotics 13(5): 303-315 (1996)

Chong Jin Ong: Distance computation between smooth convex objects. ICRA 1996: 785-790

Elmer G. Gilbert, Chong Jin Ong: New Distances for the Separation and Penetration of Objects. ICRA 1994: 579-586

Chong Jin Ong, Elmer G. Gilbert: Robot Path Planning with Penetration Growth Distance. ICRA 1994: 2146-2152