Learning curves for stochastic gradient descent in linear feedforward networks.
Werfel J, Xie X and Seung HS.
Neural Computation, 2005;17:2699-718
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Learning in neural networks by reinforcement of irregular spiking.
Xie X and Seung HS.
Phys Rev E, 2004;69:041909
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The double-ring network modeling of the head-direction system
Xie X, Hahnloser RH, and Seung HS.
Physical Review E, 2002;66:041902
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Nonlinear dynamics of direction-selective recurrent neural media
Xie X and Giese MA.
Physical Review E, 2002;65:051904
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Exact solution of the nonlinear dynamics of recurrent neural mechanisms for direction selectivity
Giese MA and Xie X
Neurocomputing 2002;44:417-422
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Learning winner-take-all competition between groups of neurons in lateral inhibitory
networks
Xie X, Hahnloser HR, and Seung HS.
Advances in Neural Information Processing Systems 2001;13:350-356
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Generating velocity tuning by asymmetric recurrent connections
Xie X and Giese MA.
Advances in Neural Information Processing Systems 2002;13:325-332
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Selectively Grouping Neurons in Recurrent Networks of Lateral Inhibition
Xie X, Hahnloser RH, and Seung HS.
Neural Computation, 2002;14:2627-2646
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Equivalence of backpropagation and contrastive Hebbian learning in a layered network
Xie X and Seung HS.
Neural Computation, 2003;16:441-454
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Threshold behavior of maximum likelihood method in population decoding
Xie X
Network: Comput. Neural Syst. 2002;13:447-456
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Spike-based learning rules and stabilization of persistent neural activity
Xie X and Seung HS
Advances in Neural Information Processing Systems 2000;12:199-205
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