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- [1] Chang J,Liu D,Xi M*,A gradient projection method for semi-supervised hypergraph clustering problems.2023,Submitted.
- [2] Zhang X,Chang J,Ge Z,Sheng Z*,A family of conjugate gradient methods with Householder transform for computing and its application to hypergraph partitioning.2023,submitted.
- [3] Feng L,Zhou G,Chang J*,An adaptive weighted self-representation method for incomplete multi-view clustering.10.48550/arXiv.2302.05563,2023,Submitted.
- [4] Chang J,Xiao B,Zhang X,A tensor optimization algorithm for computing Lagrangians of hypergraphs.Journal of Optimization Theory and Applications,2023,Accepted.
- [5] Chang J,Zhu Z,An adaptive cubic regularization algorithm for computing H- and Z-eigenvalues of real even-order supersymmetric tensors.Journal of Computational and Applied Mathematics,2023,428(-):115195.
- [6] Zhu Z,Chang J*,Solving the adaptive cubic regularization sub-problem using the Lanczos method.Symmetry,2022,14(10):2191.
- [7] Chang J,Chen Y*,Yan H,Qi L,Hypergraph clustering using a new Laplacian tensor with applications in image processing.SIAM Journal on Imaging Sciences,2020,13(3)1157--1178.
- [8] Chen Y,Chang J*,A trust region algorithm for computing extreme eigenvalues of tensors.Numerical Algebra, Control and Optimization,2020,10(4)475-485.
- [9] Chang J,Ding w,Qi L*,Yan H,Computing the P-spectral radii of uniform hypergraphs with applications.Journal of Scientific Computing,2018,(75):1–25.
- [10] Chang J,Chen Y,Qi L,Computing eigenvalues of large scale sparse tensors arising from a hypergraph.SIAM Journal on Scientific Computing,2016,38(6)A3618-A3643.
- [11] Chang J,Chen Y,Sun W*,A modified Newton's method for best rank-one approximation to tensors.Applied Mathematics and Computation,2010,216(6):1859-1867.
个人信息
- 讲师（高校）
硕士生导师
- 教师拼音名称：Chang Jingya
- 所在单位：数学与统计学院
- 联系方式：jychang@gdut.edu.cn
- 学位：理学博士学位
- 职称：讲师（高校）
- 学科：运筹学与控制论
其他联系方式
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- 邮箱:63c755bc35aad614515b4c23699266533fe3333f62cb78aa74185dddb9cc6e048e2ead074454d240a00f75fd8e5fa2936bfaac9382fef7b8d52a27172adeff9a5d7f8234efa146a733318fb30e6d34d4ea1eada2c6039f95f031fb104e09d48d8955af9afe783fe5c1cc0a28a56563c1e8773d4c46eef6851caf026a9a9dd4bb
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