James Ting-Ho Lo

Publication Activity (10 Years)

Years Active: 1972-2020
Publications (10 Years): 8

Top Topics

Error Criterion

Learning Machines

Top Venues

Publications

Huachuan Wang, James Ting-Ho Lo
Adaptively Solving the Local-Minimum Problem for Deep Neural Networks. CoRR (2020)
Huachuan Wang, James Ting-Ho Lo
Low-Order Model of Biological Neural Networks. CoRR (2020)
Yu Guo, Fei Wang, James Ting-Ho Lo
Chaotic synchronization based on neural filter. J. Frankl. Inst. 355 (4) (2018)
Yu Guo, Fei Wang, James Ting-Ho Lo
A neural filter-based scheme for synchronizing chaotic systems. ICASSP (2017)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
Solving the Local-Minimum Problem in Training Deep Learning Machines. ICONIP (1) (2017)
Yu Guo, Fei Wang, James Ting-Ho Lo
Nonlinear system identification based on recurrent neural networks with shared and specialized memories. ASCC (2017)
James Ting-Ho Lo, Yu Guo
Accommodative neural filters. IJCNN (2016)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
Training deep neural networks with gradual deconvexification. IJCNN (2016)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
The normalized risk-averting error criterion for avoiding nonglobal local minima in training neural networks. Neurocomputing 149 (2015)
Yichuan Gui, James Ting-Ho Lo, Yun Peng
A pairwise algorithm for training multilayer perceptrons with the normalized risk-averting error criterion. IJCNN (2014)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
Overcoming the local-minimum problem in training multilayer perceptrons by gradual deconvexification. IJCNN (2013)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE-MSE Training Method. ISNN (1) (2013)
James Ting-Ho Lo
A cortex-like learning machine for temporal hierarchical pattern clustering, detection, and recognition. Neurocomputing 78 (1) (2012)
James Ting-Ho Lo, Yichuan Gui, Yun Peng
Overcoming the Local-Minimum Problem in Training Multilayer Perceptrons with the NRAE Training Method. ISNN (1) (2012)
James Ting-Ho Lo
A Low-Order Model of Biological Neural Networks. Neural Comput. 23 (10) (2011)
James Ting-Ho Lo
A low-order model of biological neural networks for hierarchical or temporal pattern clustering, detection and recognition. IJCNN (2011)
James Ting-Ho Lo
Convexification for data fitting. J. Glob. Optim. 46 (2) (2010)
James Ting-Ho Lo
Convexification for data fitting. J. Glob. Optim. 46 (2) (2010)
James Ting-Ho Lo
Unsupervised Hebbian learning by recurrent multilayer neural networks for temporal hierarchical pattern recognition. CISS (2010)
James Ting-Ho Lo
Adaptive Capability of Recurrent Neural Networks with Fixed Weights for Series-Parallel System Identification. Neural Comput. 21 (11) (2009)
James Ting-Ho Lo
Probabilistic associative memories. IJCNN (2008)
James Ting-Ho Lo, Lei Yu
Overcoming recurrent neural networks' compactness limitation for neurofiltering. ICNN (1997)
James Ting-Ho Lo
Robust adaptive neurofilters with or without online weight adjustment. ICNN (1997)
James Ting-Ho Lo
Robust adaptive identification of dynamic systems by neural networks. ICNN (1997)
James Ting-Ho Lo
Adaptive system identification by nonadaptively trained neural networks. ICNN (1996)
James Ting-Ho Lo
Synthetic approach to optimal filtering. IEEE Trans. Neural Networks 5 (5) (1994)
Joseph H. Clements III, James Ting-Ho Lo
Recursive direction finding in the presence of sensor array uncertainties. ICASSP (4) (1993)
James Ting-Ho Lo, Stanley Lawrence Marple Jr.
Observability conditions for multiple signal direction finding and array sensor localization. IEEE Trans. Signal Process. 40 (11) (1992)
James Ting-Ho Lo
Backestimation for training multilayer perceptrons. ICASSP (1991)
James Ting-Ho Lo
Array sensor localization and calibration by cyclic regression. ICASSP (1990)
James Ting-Ho Lo
New maximum likelihood approach to multiple signal estimation. ICASSP (1988)
James Ting-Ho Lo, Stanley Lawrence Marple Jr.
Eigenstructure methods for array sensor localization. ICASSP (1987)
James Ting-Ho Lo, Sze-Kui Ng
Optimal functional expansion for estimation from counting observations. IEEE Trans. Inf. Theory 33 (1) (1987)
James Ting-Ho Lo, Linda R. Eshleman
Exponential Fourier densities and optimal estimation for axial processes. IEEE Trans. Inf. Theory 25 (4) (1979)
James Ting-Ho Lo, Linda R. Eshleman
Exponential Fourier densities on S2 and optimal estimation and detection for directional processes. IEEE Trans. Inf. Theory 23 (3) (1977)
James Ting-Ho Lo
Exponential Fourier densities and optimal estimation and detection on the circle. IEEE Trans. Inf. Theory 23 (1) (1977)
James Ting-Ho Lo
A general bayes rule and its application to nonlinear estimation. Inf. Sci. 8 (3) (1975)
James Ting-Ho Lo
Representation of Continuous Curves on the 3-Dimensional Rotation Group. Math. Syst. Theory 8 (4) (1975)
James Ting-Ho Lo
Signal detection for bilinear systems. Inf. Sci. 9 (3) (1975)
James Ting-Ho Lo
Signal Detection of Rotational Processes and Frequency Demodulation Inf. Control. 26 (2) (1974)
James Ting-Ho Lo
On optimal nonlinear estimation -- Part II: Discrete observation. Inf. Sci. 7 (1974)
James Ting-Ho Lo
On optimal nonlinear estimation part I: Continuous observation. Inf. Sci. 6 (1973)
James Ting-Ho Lo
Finite-dimensional sensor orbits and optimal nonlinear filtering. IEEE Trans. Inf. Theory 18 (5) (1972)