| 2007 |
|---|
| 10 | EE | Michalis K. Titsias:
The Infinite Gamma-Poisson Feature Model.
NIPS 2007 |
| 2006 |
|---|
| 9 | EE | Michalis K. Titsias,
Christopher K. I. Williams:
Sequential Learning of Layered Models from Video.
Toward Category-Level Object Recognition 2006: 577-595 |
| 8 | EE | Constantinos Constantinopoulos,
Michalis K. Titsias,
Aristidis Likas:
Bayesian Feature and Model Selection for Gaussian Mixture Models.
IEEE Trans. Pattern Anal. Mach. Intell. 28(6): 1013-1018 (2006) |
| 2005 |
|---|
| 7 | EE | Michalis K. Titsias,
Christopher K. I. Williams:
Unsupervised Learning of Multiple Aspects of Moving Objects from Video.
Panhellenic Conference on Informatics 2005: 746-756 |
| 2004 |
|---|
| 6 | EE | Christopher K. I. Williams,
Michalis K. Titsias:
Greedy Learning of Multiple Objects in Images Using Robust Statistics and Factorial Learning.
Neural Computation 16(5): 1039-1062 (2004) |
| 2003 |
|---|
| 5 | EE | Michalis K. Titsias,
Aristidis Likas:
Class Conditional Density Estimation Using Mixtures with Constrained Component Sharing.
IEEE Trans. Pattern Anal. Mach. Intell. 25(7): 924-928 (2003) |
| 2002 |
|---|
| 4 | EE | Christopher K. I. Williams,
Michalis K. Titsias:
Learning About Multiple Objects in Images: Factorial Learning without Factorial Search.
NIPS 2002: 1391-1398 |
| 3 | EE | Constantinos Constantinopoulos,
Michalis K. Titsias,
Aristidis Likas:
A Bayesian Regularization Method for the Probabilistic RBF Network.
SETN 2002: 337-345 |
| 2 | EE | Michalis K. Titsias,
Aristidis Likas:
Mixture of Experts Classification Using a Hierarchical Mixture Model.
Neural Computation 14(9): 2221-2244 (2002) |
| 2000 |
|---|
| 1 | EE | Michalis K. Titsias,
Aristidis Likas:
A Probabilistic RBF Network for Classification.
IJCNN (4) 2000: 238-243 |
