Sparse resultant perturbations

被引:0
|
作者
D'Andrea, C [1 ]
Emiris, IZ [1 ]
机构
[1] Univ Calif Berkeley, Dept Math, Berkeley, CA 94720 USA
关键词
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
We consider linear infinitesimal perturbations on sparse resultants. This yields a family of projection operators, hence a general method for handling algebraic systems in the presence of "excess" components or other degenerate inputs. The complexity is simply exponential in the dimension and polynomial in the sparse resultant degree. Our perturbation generalizes Canny's Generalized Characteristic Polynomial (GCP) for the homogeneous case, while it provides a new and faster algorithm for computing Rojas' toric perturbation. We illustrate our approach through its Maple implementation applied to specific examples. This work generalizes the linear perturbation schemes proposed in computational geometry and is also applied to the problem of rational implicitization with base points.
引用
收藏
页码:93 / 107
页数:15
相关论文
共 50 条
  • [31] Search-and-Attack: Temporally Sparse Adversarial Perturbations on Videos
    Heo, Hwan
    Ko, Dohwan
    Lee, Jaewon
    Hong, Youngjoon
    Kim, Hyunwoo J.
    IEEE ACCESS, 2021, 9 : 146938 - 146947
  • [32] Sparse Resultant-Based Minimal Solvers in Computer Vision and Their Connection with the Action Matrix
    Snehal Bhayani
    Janne Heikkilä
    Zuzana Kukelova
    Journal of Mathematical Imaging and Vision, 2024, 66 : 335 - 360
  • [33] Robust Minimax MMSE for Sparse Signal Recovery Against System Perturbations
    Liu, Hongqing
    Li, Yong
    Zhou, Yi
    Huang, Jianzhong
    PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON ESTIMATION, DETECTION AND INFORMATION FUSION ICEDIF 2015, 2015, : 18 - 23
  • [34] JOINT RECOVERY OF SPARSE SIGNALS AND PARAMETER PERTURBATIONS WITH PARAMETERIZED MEASUREMENT MODELS
    Johnson, Erik C.
    Jones, Douglas L.
    2013 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2013, : 5900 - 5904
  • [35] Modelling Cellular Perturbations with the Sparse Additive Mechanism Shift Variational Autoencoder
    Bereket, Michael
    Karaletsos, Theofanis
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023), 2023,
  • [36] Convergence of projection and contraction algorithms with outer perturbations and their applications to sparse signals recovery
    Dong, Qiao-Li
    Gibali, Aviv
    Jiang, Dan
    Ke, Shang-Hong
    JOURNAL OF FIXED POINT THEORY AND APPLICATIONS, 2018, 20 (01)
  • [37] Convergence of projection and contraction algorithms with outer perturbations and their applications to sparse signals recovery
    Qiao-Li Dong
    Aviv Gibali
    Dan Jiang
    Shang-Hong Ke
    Journal of Fixed Point Theory and Applications, 2018, 20
  • [38] A resultant system as the set of coefficients of a single resultant
    Abramov, Ya. V.
    FUNCTIONAL ANALYSIS AND ITS APPLICATIONS, 2013, 47 (03) : 233 - 237
  • [39] A resultant system as the set of coefficients of a single resultant
    Ya. V. Abramov
    Functional Analysis and Its Applications, 2013, 47 : 233 - 237
  • [40] Inference of Gene Regulatory Networks with Sparse Structural Equation Models Exploiting Genetic Perturbations
    Cai, Xiaodong
    Bazerque, Juan Andres
    Giannakis, Georgios B.
    PLOS COMPUTATIONAL BIOLOGY, 2013, 9 (05)