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Papers matching “matrix rank” 22

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Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank
2020 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Hung-Hsu Chou, Carsten Gieshoff, Johannes Maly, Holger Rauhut

2

citations
Gradient descent for deep matrix factorization: Dynamics and implicit bias towards low rank
2023 Applied and Computational Harmonic Analysis article Computer Science Stochastic Gradient Optimization Techniques

Hung-Hsu Chou, Carsten Gieshoff, Johannes Maly, Holger Rauhut

14

citations
Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias Towards Low Rank
2022 SSRN Electronic Journal preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Hung-Hsu Chou, Carsten Gieshoff, Johannes Maly, Holger Rauhut

5

citations
Weakly Supervised Regression Using Manifold Regularization and Low-Rank Matrix Representation
2021 Lecture notes in computer science conference-paper Computer Science Face and Expression Recognition

Vladimir Berikov, Alexander Litvinenko

5

citations
Julia code for "Low-Rank Eigenvalue Solvers for Block-Sparse Matrix Product States"
2026 Zenodo (CERN European Organization for Nuclear Research) software Computer Science Matrix Theory and Algorithms Open access

Markus Bachmayr, M Götte, Sebastian Krämer

0

citations
Julia code for "Low-Rank Eigenvalue Solvers for Block-Sparse Matrix Product States"
2026 Zenodo (CERN European Organization for Nuclear Research) software Computer Science Matrix Theory and Algorithms Open access

Markus Bachmayr, M Götte, Sebastian Krämer

0

citations
Low-rank eigenvalue solvers for block-sparse matrix product states
2026 arXiv (Cornell University) preprint Computer Science Matrix Theory and Algorithms Open access

Markus Bachmayr, Sebastian Krämer, Max J. Pfeffer

0

citations
Solving weakly supervised regression problem using low-rank manifold regularization
2021 arXiv (Cornell University) preprint Computer Science Machine Learning and Algorithms Open access

Vladimir Berikov, Alexander Litvinenko

2

citations
Efficient MPS representations and quantum circuits from the Fourier modes of classical image data
2024 Quantum article Computer Science Quantum Computing Algorithms and Architecture Open access

Carlos A. Riofrío, Elvira Shishenina, Frank Pollmann

13

citations
Proof of a Conjectured 0-Rényi Entropy Inequality With Applications to Multipartite Entanglement
2022 IEEE Transactions on Information Theory article Computer Science Quantum Information and Cryptography Open access

Zhiwei Song, Lin Chen, Yize Sun, Mengyao Hu

7

citations
The loss landscape of deep linear neural networks: a second-order analysis
2021 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

El Mehdi Achour, François Malgouyres, Sébastien Gerchinovitz

1

citations
On a Weakly Supervised Classification Problem
2022 Lecture notes in computer science conference-paper Computer Science Machine Learning and Algorithms

Vladimir Berikov, Alexander Litvinenko, Игорь Алексеевич Пестунов, Yuriy Sinyavskiy

0

citations
Convergence of gradient descent for learning linear neural networks
2024 Advances in Continuous and Discrete Models article Computer Science Stochastic Gradient Optimization Techniques Open access

Gabin Maxime Nguegnang, Holger Rauhut, Ulrich Terstiege

10

citations
Convergence of gradient descent for learning linear neural networks
2021 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Gabin Maxime Nguegnang, Holger Rauhut, Ulrich Terstiege

1

citations
Nicht-parametrische Schätzung von Kundensegmenten mit Paneldaten
2021 RWTH Publications (RWTH Aachen) dissertation Computer Science Bayesian Methods and Mixture Models Open access

Johannes Ferdinand Jörg

1

citations
Learning deep linear neural networks: Riemannian gradient flows and convergence to global minimizers
2021 Information and Inference A Journal of the IMA article Computer Science Stochastic Gradient Optimization Techniques Open access

Bubacarr Bah, Holger Rauhut, Ulrich Terstiege, Michael Westdickenberg

29

citations
A Test for FLOPs as a Discriminant for Linear Algebra Algorithms
2022 IEEE International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) conference-paper Computer Science Matrix Theory and Algorithms Open access

Aravind Sankaran, Paolo Bientinesi

1

citations
QuantumSavory/QuantumClifford.jl: v0.11.0
2026 Zenodo (CERN European Organization for Nuclear Research) software Computer Science Quantum Computing Algorithms and Architecture Open access

Stefan Krastanov, Feroz Ahmed Mian, Zhongyi Ni, Kanyang Ying, Praveen Viswanathan, Shayan Pardis, +21 more

0

citations
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
2023 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Semih Çaycı, Atilla Eryılmaz

2

citations
On Deciding Constant Runtime of Linear Loops
2026 arXiv (Cornell University) preprint Computer Science Logic, programming, and type systems Open access

Florian Frohn, Jürgen Giesl, Peter Giesl, Nils Lommen

0

citations
On Deciding Constant Runtime of Linear Loops
2026 arXiv (Cornell University) preprint Computer Science Logic, programming, and type systems Open access

Florian Frohn, Jürgen Giesl, Peter Giesl, Nils Lommen

0

citations
Decoder Comparability Across Quantum Software Stacks: Repeated-Round Surface and Digitized-GKP Syndrome Replay
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Dennis Delali Kwesi Wayo, Chinonso Onah, Rodrigo Alves Dias, Leonardo Goliatt, Zaher Mundher Yaseen Sven Groppe

0

citations

22 results