Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
An improved method for finding nearest neighbors
Pattern Recognition Letters
Neural Computation
Local algorithms for pattern recognition and dependencies estimation
Neural Computation
Distributed and local neural classifiers for phoneme recognition
Pattern Recognition Letters
The nature of statistical learning theory
The nature of statistical learning theory
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Pattern Recognition Using a New Transformation Distance
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Incorporating Invariances in Support Vector Learning Machines
ICANN 96 Proceedings of the 1996 International Conference on Artificial Neural Networks
Nonnegative Least-Squares Methods for the Classification of High-Dimensional Biological Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
| Hi-index | 0.10 |
Surprisingly simple local learning algorithms are known to outperform many other global non-linear machines. Unfortunately, these algorithms are computationally costly. A means of combining both learning approaches is proposed in and shown to enhance performance.