| 2006 |
|---|
| 7 | | Te Ming Huang,
Vojislav Kecman,
Ivica Kopriva:
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning.
Springer 2006 |
| 6 | EE | Te Ming Huang,
Vojislav Kecman:
Semi-supervised learning from unbalanced labeled data: An improvement.
KES Journal 10(1): 21-27 (2006) |
| 2005 |
|---|
| 5 | EE | Te Ming Huang,
Vojislav Kecman:
Gene Extraction for Cancer Diagnosis by Support Vector Machines.
ICANN (1) 2005: 617-624 |
| 4 | EE | Te Ming Huang,
Vojislav Kecman:
Gene extraction for cancer diagnosis by support vector machines - An improvement.
Artificial Intelligence in Medicine 35(1-2): 185-194 (2005) |
| 2004 |
|---|
| 3 | EE | Te Ming Huang,
Vojislav Kecman:
Bias Term b in SVMs Again.
ESANN 2004: 441-448 |
| 2 | EE | Te Ming Huang,
Vojislav Kecman:
Semi-supervised Learning from Unbalanced Labeled Data - An Improvement.
KES 2004: 802-808 |
| 2003 |
|---|
| 1 | EE | Vojislav Kecman,
Michael Vogt,
Te Ming Huang:
On the equality of kernel AdaTron and sequential minimal optimization in classification and regression tasks and alike algorithms for kernel machines.
ESANN 2003: 215-222 |
