Andrew D. Back

33 papers B 1Journal 20Unranked 9
YearRankTypeTitle / Venue / Authors
2023 — conf
Estimation of Statistical Manifold Properties of Natural Sequences using Information Topology.
SSP
Andrew D. Back, Janet Wiles
2022 J jnl
An Information Theoretic Approach to Symbolic Learning in Synthetic Languages.
Entropy
Andrew D. Back, Janet Wiles
2022 J jnl
Estimating Sentence-like Structure in Synthetic Languages Using Information Topology.
Entropy
Andrew D. Back, Janet Wiles
2021 J jnl
Entropy Estimation Using a Linguistic Zipf-Mandelbrot-Li Model for Natural Sequences.
Entropy
Andrew D. Back, Janet Wiles
2020 — conf
A Plan for Developing an Auslan Communication Technologies Pipeline.
ECCV Workshops (2)
Jessica Korte, Axel Bender, Guy Edward Gallasch, Janet Wiles, Andrew D. Back
2020 J jnl
Transitive Entropy - A Rank Ordered Approach for Natural Sequences.
IEEE J. Sel. Top. Signal Process.
Andrew D. Back, Daniel Angus, Janet Wiles
2019 J jnl
Determining the Number of Samples Required to Estimate Entropy in Natural Sequences.
IEEE Trans. Inf. Theory
Andrew D. Back, Daniel Angus, Janet Wiles
2018 J jnl
Determining the Number of Samples Required to Estimate Entropy in Natural Sequences.
CoRR
Andrew D. Back, Daniel Angus, Janet Wiles
2018 — conf
PauseCode: Computational Conversation Timing Analysis.
MA3HMI@ICMI
Daniel Angus, Yeyang Yu, Paul Vrbik, Andrew D. Back, Janet Wiles
2012 — ch.
Neural Network Classification and Prior Class Probabilities.
Neural Networks: Tricks of the Trade (2nd ed.)
Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles
2006 J jnl
Input Variable Selection: Mutual Information and Linear Mixing Measures.
IEEE Trans. Knowl. Data Eng.
Thomas Trappenberg, Jie Ouyang, Andrew D. Back
2002 J jnl
Universal Approximation of Multiple Nonlinear Operators by Neural Networks.
Neural Comput.
Andrew D. Back, Tianping Chen
2001 J jnl
A spiking neural network architecture for nonlinear function approximation.
Neural Networks
Nicolangelo Iannella, Andrew D. Back
2001 J jnl
Selecting inputs for modeling using normalized higher order statistics and independent component analysis.
IEEE Trans. Neural Networks
Andrew D. Back, Thomas Trappenberg
2000 — conf
A Classification Scheme for Applications with Ambiguous Data.
IJCNN (6)
Thomas Trappenberg, Andrew D. Back
1999 J jnl
Alternative discrete-time operators: an algorithm for optimal selection of parameters.
IEEE Trans. Signal Process.
Andrew D. Back, Bill G. Horne, Ah Chung Tsoi, C. Lee Giles
1999 B conf
Input variable selection using independent component analysis.
IJCNN
Andrew D. Back, Thomas Trappenberg
1998 J jnl
A Low Sensitivity Recurrent Neural Network.
Neural Comput.
Andrew D. Back, Ah Chung Tsoi
1998 — conf
What drives stock returns?-an independent component analysis.
CIFEr
Andrew D. Back, Andreas S. Weigend
1997 J jnl
A First Application of Independent Component Analysis to Extracting Structure from Stock Returns.
Int. J. Neural Syst.
Andrew D. Back, Andreas S. Weigend
1997 — conf
Approximation of Hybrid Systems by Neural Networks.
ICONIP (1)
Andrew D. Back, Tianping Chen
1997 — conf
Blind Source Separation and Deconvolution of Fast Sampled Signals.
ICONIP (1)
Andrew D. Back, Andrzej Cichocki
1997 J jnl
Discrete time recurrent neural network architectures: A unifying review.
Neurocomputing
Ah Chung Tsoi, Andrew D. Back
1997 J jnl
Face recognition: a convolutional neural-network approach.
IEEE Trans. Neural Networks
Steve Lawrence, C. Lee Giles, Ah Chung Tsoi, Andrew D. Back
1997 J jnl
On the distribution of performance from multiple neural-network trials.
IEEE Trans. Neural Networks
Steve Lawrence, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles
1996 — ch.
Neural Network Classification and Prior Class Probabilities.
Neural Networks: Tricks of the Trade
Steve Lawrence, Ian Burns, Andrew D. Back, Ah Chung Tsoi, C. Lee Giles
1995 — conf
The Gamma MLP for Speech Phoneme Recognition.
NIPS
Steve Lawrence, Ah Chung Tsoi, Andrew D. Back
1994 — conf
A Comparison of Discrete-Time Operator Models and for Nonlinear System Identification.
NIPS
Andrew D. Back, Ah Chung Tsoi
1994 J jnl
Locally recurrent globally feedforward networks: a critical review of architectures.
IEEE Trans. Neural Networks
Ah Chung Tsoi, Andrew D. Back
1993 J jnl
A Simplified Gradient Algorithm for IIR Synapse Multilayer Perceptrons.
Neural Comput.
Andrew D. Back, Ah Chung Tsoi
1992 J jnl
An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons.
Neural Comput.
Andrew D. Back, Ah Chung Tsoi
1992 — —
New techniques for nonlinear system identification : a rapprochement between neural networks and linear systems / by Andrew D. Back
Andrew D. Back
1991 J jnl
FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling.
Neural Comput.
Andrew D. Back, Ah Chung Tsoi