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ORCIDJoe Kileel 0001
Person information
- affiliation: University of Texas at Austin, Department of Mathematics, USA
- affiliation: University of Texas at Austin, Oden Institute for Computational Engineering and Sciences, USA
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Books and Theses
- 2017
[b1]Joseph David Kileel:
Algebraic Geometry for Computer Vision. University of California, Berkeley, USA, 2017
Journal Articles
- 2023
- [j6]Eitan Levin
, Joe Kileel, Nicolas Boumal:
Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy. Math. Program. 199(1): 831-864 (2023) - [j5]Yifan Zhang, Joe Kileel:
Moment Estimation for Nonparametric Mixture Models through Implicit Tensor Decomposition. SIAM J. Math. Data Sci. 5(4): 1130-1159 (2023) - 2018
- [j4]Joe Kileel, Zuzana Kukelova, Tomás Pajdla, Bernd Sturmfels:
Distortion Varieties. Found. Comput. Math. 18(4): 1043-1071 (2018) - [j3]Gunnar Fløystad, Joe Kileel, Giorgio Ottaviani:
The Chow form of the essential variety in computer vision. J. Symb. Comput. 86: 97-119 (2018) - 2017
- [j2]Joe Kileel:
Minimal Problems for the Calibrated Trifocal Variety. SIAM J. Appl. Algebra Geom. 1(1): 575-598 (2017) - 2016
- [j1]Michael Joswig, Joe Kileel, Bernd Sturmfels, André Wagner:
Rigid multiview varieties. Int. J. Algebra Comput. 26(4): 775-788 (2016)
Conference and Workshop Papers
- 2023
- [c7]Yulia Alexandr, Joe Kileel, Bernd Sturmfels:
Moment Varieties for Mixtures of Products. ISSAC 2023: 53-60 - 2022
- [c6]Hongyi Fan, Joe Kileel, Benjamin B. Kimia:
On the Instability of Relative Pose Estimation and RANSAC's Role. CVPR 2022: 8925-8933 - 2021
- [c5]Joe Kileel, Timo Klock, João M. Pereira:
Landscape analysis of an improved power method for tensor decomposition. NeurIPS 2021: 6253-6265 - 2020
- [c4]Nathan Zelesko, Amit Moscovich, Joe Kileel, Amit Singer:
Earthmover-Based Manifold Learning for Analyzing Molecular Conformation Spaces. ISBI 2020: 1715-1719 - 2019
- [c3]Joe Kileel, Matthew Trager, Joan Bruna:
On the Expressive Power of Deep Polynomial Neural Networks. NeurIPS 2019: 10310-10319 - 2018
- [c2]Eitan Levin, Tamir Bendory, Nicolas Boumal, Joe Kileel, Amit Singer:
3D ab initio modeling in cryo-EM by autocorrelation analysis. ISBI 2018: 1569-1573 - 2017
- [c1]Zuzana Kukelova, Joe Kileel, Bernd Sturmfels, Tomás Pajdla:
A Clever Elimination Strategy for Efficient Minimal Solvers. CVPR 2017: 3605-3614
Informal and Other Publications
- 2024
- [i25]Joe Kileel, Nicholas F. Marshall, Oscar Mickelin, Amit Singer:
Fast expansion into harmonics on the ball. CoRR abs/2406.05922 (2024) - 2023
- [i24]Paulina Hoyos, Joe Kileel:
Diffusion Maps for Group-Invariant Manifolds. CoRR abs/2303.16169 (2023) - [i23]Hongyi Fan, Joe Kileel, Benjamin B. Kimia:
Condition numbers in multiview geometry, instability in relative pose estimation, and RANSAC. CoRR abs/2310.02719 (2023) - [i22]Yifan Zhang, Joe Kileel:
Covering Number of Real Algebraic Varieties and Beyond: Improved Bounds and Applications. CoRR abs/2311.05116 (2023) - 2022
- [i21]João M. Pereira, Joe Kileel, Tamara G. Kolda:
Tensor Moments of Gaussian Mixture Models: Theory and Applications. CoRR abs/2202.06930 (2022) - [i20]Ruhui Jin, Joe Kileel, Tamara G. Kolda, Rachel A. Ward:
Scalable symmetric Tucker tensor decomposition. CoRR abs/2204.10824 (2022) - [i19]Eitan Levin, Joe Kileel, Nicolas Boumal:
The effect of smooth parametrizations on nonconvex optimization landscapes. CoRR abs/2207.03512 (2022) - [i18]Tamir Bendory, Yuehaw Khoo, Joe Kileel, Oscar Mickelin, Amit Singer:
Autocorrelation analysis for cryo-EM with sparsity constraints: Improved sample complexity and projection-based algorithms. CoRR abs/2209.10531 (2022) - [i17]Joe Kileel, Kathlén Kohn:
Snapshot of Algebraic Vision. CoRR abs/2210.11443 (2022) - [i16]Yifan Zhang, Joe Kileel:
Moment Estimation for Nonparametric Mixture Models Through Implicit Tensor Decomposition. CoRR abs/2210.14386 (2022) - 2021
- [i15]Yossi Arjevani, Joan Bruna, Michael Field, Joe Kileel, Matthew Trager, Francis Williams:
Symmetry Breaking in Symmetric Tensor Decomposition. CoRR abs/2103.06234 (2021) - [i14]Eitan Levin, Joe Kileel, Nicolas Boumal:
Finding stationary points on bounded-rank matrices: A geometric hurdle and a smooth remedy. CoRR abs/2107.03877 (2021) - [i13]Joe Kileel, Timo Klock, João M. Pereira:
Landscape analysis of an improved power method for tensor decomposition. CoRR abs/2110.15821 (2021) - [i12]Hongyi Fan, Joe Kileel, Benjamin B. Kimia:
On the Instability of Relative Pose Estimation and RANSAC's Role. CoRR abs/2112.14651 (2021) - 2020
- [i11]Joe Kileel, Amit Moscovich, Nathan Zelesko, Amit Singer:
Manifold learning with arbitrary norms. CoRR abs/2012.14172 (2020) - 2019
- [i10]Joe Kileel, Matthew Trager, Joan Bruna:
On the Expressive Power of Deep Polynomial Neural Networks. CoRR abs/1905.12207 (2019) - [i9]Nir Sharon, Joe Kileel, Yuehaw Khoo, Boris Landa, Amit Singer:
Method of moments for 3-D single particle ab initio modeling with non-uniform distribution of viewing angles. CoRR abs/1907.05377 (2019) - [i8]Nathan Zelesko, Amit Moscovich, Joe Kileel, Amit Singer:
Earthmover-based manifold learning for analyzing molecular conformation spaces. CoRR abs/1911.06107 (2019) - [i7]Joe Kileel, João M. Pereira:
Subspace power method for symmetric tensor decomposition and generalized PCA. CoRR abs/1912.04007 (2019) - 2017
- [i6]Zuzana Kukelova, Joe Kileel, Bernd Sturmfels, Tomás Pajdla:
A clever elimination strategy for efficient minimal solvers. CoRR abs/1703.05289 (2017) - 2016
- [i5]Gunnar Fløystad, Joe Kileel, Giorgio Ottaviani:
The Chow Form of the Essential Variety in Computer Vision. CoRR abs/1604.04372 (2016) - [i4]Joe Kileel, Zuzana Kukelova, Tomás Pajdla, Bernd Sturmfels:
Distortion Varieties. CoRR abs/1610.01860 (2016) - [i3]Justin Chen, Joe Kileel:
Numerical Implicitization for Macaulay2. CoRR abs/1610.03034 (2016) - [i2]Joe Kileel:
Minimal Problems for the Calibrated Trifocal Variety. CoRR abs/1611.05947 (2016) - 2015
- [i1]Michael Joswig, Joe Kileel, Bernd Sturmfels, André Wagner:
Rigid Multiview Varieties. CoRR abs/1509.03257 (2015)
Coauthor Index
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