 | 2009 |
| 20 |  | 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) |
| 19 |  | 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) |
| 2008 |
| 18 |  | Chen Wang,
Chong Jin Ong,
Melvyn Sim:
Constrained linear system under disturbance feedback: Convergence with probability one.
CDC 2008: 2820-2825 |
| 17 |  | Chen Wang,
Chong Jin Ong,
Melvyn Sim:
Constrained linear system with disturbance: Convergence under disturbance feedback.
Automatica 44(10): 2583-2587 (2008) |
| 16 |  | 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) |
| 2006 |
| 15 |  | 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 |
| 14 |  | 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 |
| 13 |  | Chong Jin Ong,
D. 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) |
| 12 |  | Chong Jin Ong,
Elmer G. Gilbert:
The minimal disturbance invariant set: Outer approximations via its partial sums.
Automatica 42(9): 1563-1568 (2006) |
| 11 |  | 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) |
| 10 |  | 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) |
| 2003 |
| 9 |  | 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 |
| 8 |  | Wei Chu,
S. Sathiya Keerthi,
Chong Jin Ong:
Bayesian Trigonometric Support Vector Classifier.
Neural Computation 15(9): 2227-225 (2003) |
| 2002 |
| 7 |  | 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) |
| 2001 |
| 6 |  | Wei Chu,
S. Sathiya Keerthi,
Chong Jin Ong:
A Unified Loss Function in Bayesian Framework for Support Vector Regression.
ICML 2001: 51-58 |
| 1999 |
| 5 |  | S. Sathiya Keerthi,
Chong Jin Ong,
Eugene Huang,
Elmer G. Gilbert:
EquiDistance Diagram: A New Roadmap Method for Path Planning.
ICRA 1999: 682-687 |
| 1998 |
| 4 |  | Chong Jin Ong,
Eugene Huang:
An Incremental Version of Growth Distance.
ICRA 1998: 3671-3677 |
| 1997 |
| 3 |  | Chong Jin Ong:
On the Quantification of Penetration between General Objects.
I. J. Robotic Res. 16(3): 400-409 (1997) |
| 1994 |
| 2 |  | Chong Jin Ong,
Elmer G. Gilbert:
Robot Path Planning with Penetration Growth Distance.
ICRA 1994: 2146-2152 |
| 1 |  | Elmer G. Gilbert,
Chong Jin Ong:
New Distances for the Separation and Penetration of Objects.
ICRA 1994: 579-586 |