黄海平 - 中山大学

个人简介

主要经历: 2018.03- 中山大学百人计划副教授 2014.08-2018.03 日本理化学研究所研究科学家（Research Scientist) 2012.08-2014.08 日本学术振兴会外国人特别研究员（JSPS postdoctoral fellow） 2011.08-2012.08 香港科技大学访问学者（Visiting Scholar） 2006.09-2011.07 中国科学院理论物理研究所博士生 2002.09-2006.06 中山大学理工学院物理学专业本科生

研究领域

神经计算的统计物理学，具体的研究方向－ a. 无序系统的统计物理: 复本理论, 空腔方法, 物理启发的消息传递算法，描述非线性动力学的动力学平均场理论; b. 神经网络的理论和计算模型: 监督学习神经网络，受限玻尔兹曼机的平均场理论, 深度无监督学习, 循环神经网络的平均场理论及其神经科学原理; 生物神经网络的相变理论。

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

[1] H. Huang, Role of zero synapses in unsupervised feature learning, 2018 J. Phys. A: Math. Theor. 51 08LT01. Published as a LETTER. [2] H. Huang, Statistical mechanics of unsupervised feature learning in a restricted Boltzmann machine with binary synapses, J. Stat. Mech. (2017) 053302. Recommended in Quora. [3] H. Huang, Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons, J. Stat. Mech. (2017) 033501. [4] H. Huang* and T. Toyoizumi, Clustering of neural codewords revealed by a first-order phase transition, Phys. Rev. E 93, 062416 (2016). Selected as one of the most interesting and intriguing arXiv papers from the past week by MIT Technology Review. [5] H. Huang* and T. Toyoizumi, Unsupervised feature learning from finite data by message passing: discontinuous versus continuous phase transition, Phys. Rev. E 94, 062310 (2016). [6] H. Huang, Effects of hidden nodes on network structure inference, J. Phys. A: Math. Theor. 48 355002 (2015). [7] H. Huang* and T. Toyoizumi, Advanced mean field theory of the restricted Boltzmann machine, Phys. Rev. E 91, 050101(R) (2015). Published as a Rapid Communication. [8] H. Huang* and Y. Kabashima, Origin of the computational hardness for learning with binary synapses, Phys. Rev. E 90, 052813 (2014). Solved a long standing problem—why is a binary perceptron hard to learn [9] H. Huang* and Y. Kabashima, Dynamics of asymmetric kinetic Ising systems revisited. J. Stat. Mech.: Theory Exp. P05020 (2014). [10] H. Huang*, K. Y. Michael Wong and Y. Kabashima, Entropy landscape of solutions in the binary perceptron problem, J. Phys. A: Math. Theor. 46 375002 (2013). Selected in the Research Highlights section of J. Phys. A. [11] H. Huang, Sparse Hopfield network reconstruction with L1 regularization. Eur. Phys. J. B 86, 484 (2013). [12] H. Huang*, and Y. Kabashima, Adaptive Thouless-Anderson-Palmer approach to inverse Ising problems with quenched random fields. Phys. Rev. E 87, 062129 (2013). [13] H. Huang* and H. Zhou, Counting solutions from finite samplings. Phys. Rev. E 85, 026118 (2012). [14] H. Huang* and H. Zhou, Combined local search strategy for learning in networks of binary synapses. Europhysics Letters 96, 58003 (2011).