| 2006 |
|---|
| 11 | EE | Thomas J. Sullivan,
Virginia R. de Sa:
A model of surround suppression through cortical feedback.
Neural Networks 19(5): 564-572 (2006) |
| 10 | EE | Thomas J. Sullivan,
Virginia R. de Sa:
Homeostatic synaptic scaling in self-organizing maps.
Neural Networks 19(6-7): 734-743 (2006) |
| 9 | EE | Thomas J. Sullivan,
Virginia R. de Sa:
A self-organizing map with homeostatic synaptic scaling.
Neurocomputing 69(10-12): 1183-1186 (2006) |
| 2003 |
|---|
| 8 | EE | Virginia R. de Sa:
Sensory Modality Segregation.
NIPS 2003 |
| 7 | EE | Rich Caruana,
Virginia R. de Sa:
Benefitting from the Variables that Variable Selection Discards.
Journal of Machine Learning Research 3: 1245-1264 (2003) |
| 2001 |
|---|
| 6 | EE | Virginia R. de Sa,
David J. C. MacKay:
Model fitting as an aid to bridge balancing in neuronal recording.
Neurocomputing 38-40: 1651-1656 (2001) |
| 1998 |
|---|
| 5 | | Virginia R. de Sa,
Dana H. Ballard:
Category Learning Through Multi-Modality Sensing.
Neural Computation 10(5): 1097-1117 (1998) |
| 1997 |
|---|
| 4 | | Virginia R. de Sa,
R. Christopher DeCharms,
Michael Merzenich:
Using Helmholtz Machines to Analyze Multi-channel Neuronal Recordings.
NIPS 1997 |
| 1996 |
|---|
| 3 | EE | Rich Caruana,
Virginia R. de Sa:
Promoting Poor Features to Supervisors: Some Inputs Work Better as Outputs.
NIPS 1996: 389-395 |
| 1993 |
|---|
| 2 | EE | Virginia R. de Sa:
Learning Classification with Unlabeled Data.
NIPS 1993: 112-119 |
| 1992 |
|---|
| 1 | EE | Virginia R. de Sa,
Dana H. Ballard:
A Note on Learning Vector Quantization.
NIPS 1992: 220-227 |
