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Variational Gaussian Topic Model with Invertible Neural Projections

May 21, 2021
Rui Wang, Deyu Zhou, Yuxuan Xiong, Haiping Huang

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Ensemble perspective for understanding temporal credit assignment

Feb 07, 2021
Wenxuan Zou, Chan Li, Haiping Huang

* 17 pages, 18 figures, comments are welcome 

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Data-driven effective model shows a liquid-like deep learning

Jul 16, 2020
Wenxuan Zou, Haiping Huang

* 14 pages, 7 figures, comments are welcome 

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Relationship between manifold smoothness and adversarial vulnerability in deep learning with local errors

Jul 04, 2020
Zijian Jiang, Jianwen Zhou, Haiping Huang

* 10 pages, 8 figures, comments are welcome 

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Weakly-correlated synapses promote dimension reduction in deep neural networks

Jun 20, 2020
Jianwen Zhou, Haiping Huang

* 21 pages, 8 figures 

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Classification and Recognition of Encrypted EEG Data Neural Network

Jun 15, 2020
Yongshuang Liu, Haiping Huang, Fu Xiao, Reza Malekian, Wenming Wang

* JISA, 2020 

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Learning credit assignment

Jan 10, 2020
Chan Li, Haiping Huang

* 5 pages, 3 figures, a generalized BackProp proposed to learn credit assignment from an network ensemble perspective 

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How data, synapses and neurons interact with each other: a variational principle marrying gradient ascent and message passing

Nov 11, 2019
Haiping Huang

* 8 pages, 3 figures, a mean-field framework proposed for unsupervised learning in RBM with discrete synapses, which was previously out of reach 

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Statistical physics of unsupervised learning with prior knowledge in neural networks

Nov 06, 2019
Tianqi Hou, Haiping Huang

* 13 pages, 2 figures with supplemental material 

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Minimal model of permutation symmetry in unsupervised learning

Apr 30, 2019
Tianqi Hou, K. Y. Michael Wong, Haiping Huang

* 33 pages, 103 equations, 4 figures 

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Random active path model of deep neural networks with diluted binary synapses

Sep 26, 2018
Haiping Huang, Alireza Goudarzi

* Phys. Rev. E 98, 042311 (2018) 
* 10 pages, 5 figures, with Supplemental Material (upon request) 

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Mean-field theory of input dimensionality reduction in unsupervised deep neural networks

Jan 12, 2018
Haiping Huang

* 5 pages, 3 figures, a physics explanation of decorrelation and dimensionality reduction is added 

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Role of zero synapses in unsupervised feature learning

Jan 10, 2018
Haiping Huang

* 6 pages, 4 figures, to appear in J. Phys A as a LETTER 

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Reinforced stochastic gradient descent for deep neural network learning

Nov 22, 2017
Haiping Huang, Taro Toyoizumi

* 12 pages and 9 figures, nearly final version as a technical report 

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Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses

Mar 07, 2017
Haiping Huang

* J. Stat. Mech. (2017) 053302 
* 24 pages, 9 figures, results added 

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Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition

Nov 11, 2016
Haiping Huang, Taro Toyoizumi

* Phys. Rev. E 94, 062310 (2016) 
* 8 pages, 7 figures (5 pages, 4 figures in the main text and 3 pages of appendix) 

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Advanced Mean Field Theory of Restricted Boltzmann Machine

May 02, 2015
Haiping Huang, Taro Toyoizumi

* Phys. Rev. E 91, 050101 (2015) 
* 5 pages, 4 figures, accepted by Phys Rev E (Rapid Communication) 

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Origin of the computational hardness for learning with binary synapses

Aug 08, 2014
Haiping Huang, Yoshiyuki Kabashima

* Phys. Rev. E 90, 052813 (2014) 
* 9 pages, 1 figure 

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Entropy landscape of solutions in the binary perceptron problem

Aug 09, 2013
Haiping Huang, K. Y. Michael Wong, Yoshiyuki Kabashima

* J. Phys. A: Math. Theor. 46 (2013) 375002 
* 21 pages, 6 figures, version accepted by Journal of Physics A: Mathematical and Theoretical 

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Learning by random walks in the weight space of the Ising perceptron

May 30, 2010
Haiping Huang, Haijun Zhou

* J. Stat. Mech.: Theory Exp. P08014 (2010) 
* 12 pages, 4 figures, An extensively revised version 

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