2007 |
13 | EE | Abraham K. Ishihara,
Johan van Doornik,
Terence D. Sanger:
A Direct Measurement of Internal Model Learning Rates in a Visuomotor Tracking Task.
ICANN (2) 2007: 39-48 |
2006 |
12 | EE | Johan van Doornik,
Abraham K. Ishihara,
Terence D. Sanger:
Uniform Boundedness of Feedback Error Learning for a Class of Stochastic Nonlinear Systems.
ICARCV 2006: 1-5 |
11 | EE | Abraham K. Ishihara,
Johan van Doornik,
Terence D. Sanger:
Failure Modes in Feedback Error Learning.
IJCNN 2006: 277-284 |
2004 |
10 | EE | Terence D. Sanger:
Failure of Motor Learning for Large Initial Errors.
Neural Computation 16(9): 1873-1886 (2004) |
1998 |
9 | | Terence D. Sanger:
Probability Density Methods for Smooth Function Approximation and Learning in Populations of Tuned Spiking Neurons.
Neural Computation 10(6): 1567-1586 (1998) |
1994 |
8 | EE | Terence D. Sanger:
Optimal Movement Primitives.
NIPS 1994: 1023-1030 |
1993 |
7 | EE | Terence D. Sanger:
Two Iterative Algorithms for Computing the Singular Value Decomposition from Input/Output Samples.
NIPS 1993: 144-151 |
6 | EE | Terence D. Sanger:
Optimal Unsupervised Motor Learning Predicts the Internal Representation of Barn Owl Head Movements.
NIPS 1993: 614-621 |
1992 |
5 | EE | Terence D. Sanger:
A Practice Strategy for Robot Learning Control.
NIPS 1992: 335-341 |
1991 |
4 | EE | Terence D. Sanger,
Richard S. Sutton,
Christopher J. Matheus:
Iterative Construction of Sparse Polynomial Approximations.
NIPS 1991: 1064-1071 |
1990 |
3 | EE | Terence D. Sanger:
Basis-Function Trees as a Generalization of Local Variable Selection Methods.
NIPS 1990: 700-706 |
1989 |
2 | EE | Terence D. Sanger:
Optimal unsupervised learning in a single-layer linear feedforward neural network.
Neural Networks 2(6): 459-473 (1989) |
1988 |
1 | EE | Terence D. Sanger:
An Optimality Principle for Unsupervised Learning.
NIPS 1988: 11-19 |