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Papers matching “linear convergence” 13

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Convergence of gradient based training for linear Graph Neural Networks
2025 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Dhiraj Patel, Anton Savostianov, Michael T. Schaub

0

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
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
A Mean-Field Theory of Transformers: Well-Posedness of the Coupled Data--Parameter Dynamics and Global Convergence of Training
2026 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Michael Herty, Hailiang Liu

0

citations
A Newton method for solving locally definite multiparameter eigenvalue problems by multiindex
2024 arXiv (Cornell University) preprint Computer Science Matrix Theory and Algorithms Open access

Henrik Eisenmann

0

citations
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
2022 SSRN Electronic Journal preprint Computer Science Stochastic Gradient Optimization Techniques Open access

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

5

citations
Riemannian gradient descent-based quantum algorithms for ground state preparation with guarantees
2025 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Mahum Pervez, Ariq Haqq, Nathan A. McMahon, Christian Arenz

0

citations
Only Strict Saddles in the Energy Landscape of Predictive Coding Networks?
2024 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Francesco Innocenti, El Mehdi Achour, Ryan R. Singh, Christopher L. Buckley

0

citations
Graph Neural Networks Do Not Always Oversmooth
2024 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Bastian Epping, Alexandre René, Moritz Helias, Michael T. Schaub

3

citations
Constant-time equilibration of observables under rapid Lindbladian dynamics
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Štěpán Šmíd, Richard Meister, Mario Berta, Roberto Bondesan

0

citations
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
2024 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Michael Scholkemper, Xinyi Wu, Ali Jadbabaie, Michael T. Schaub

1

citations
An Optimal Factorization Preconditioner for Periodic Schr\"odinger Eigenstates in Anisotropically Expanding Domains
2021 arXiv (Cornell University) preprint Computer Science Matrix Theory and Algorithms Open access

Benjamin Stamm, Lambert Theisen

0

citations

13 results