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Papers matching “stochastic gradient descent” 29

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Stochastic Gradient Descent with Momentum: Analysis and Synthesis via Integral Quadratic Constraints
2026 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Dennis Gramlich, Carsten W. Scherer, Christian Ebenbauer

0

citations
Stochastic Gradient Descent for Constrained Optimization Based on Adaptive Relaxed Barrier Functions
2025 IEEE Control Systems Letters article Engineering Industrial Vision Systems and Defect Detection

Naum Dimitrieski, Jing Cao, Christian Ebenbauer

3

citations
Deep Relaxation of Controlled Stochastic Gradient Descent via Singular Perturbations
2024 SIAM Journal on Control and Optimization article Mathematics Numerical methods in inverse problems Open access

Martino Bardi, Hicham Kouhkouh

4

citations
A Poisson Jump-driven SDE Approach to Distributed Gradient Descent with Sparse Communication
2025 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

John Paul Strachan, Christian Ebenbauer

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
Finite-Time Analysis of Gradient Descent for Shallow Transformers
2026 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Enes Arda, Semih Çaycı, Atilla Eryılmaz

0

citations
Complexity Analysis of stochastic gradient methods for PDE-constrained optimal Control Problems with uncertain parameters
2021 ESAIM Mathematical Modelling and Numerical Analysis article Decision Sciences Probabilistic and Robust Engineering Design Open access

Matthieu Martin, Sebastian Krumscheid, Fabio Nobile

27

citations
Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank
2020 arXiv (Cornell University) preprint Engineering Sparse and Compressive Sensing Techniques Open access

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

2

citations
Forecasting future bigrams and promising patents: introducing text-based link prediction
2022 foresight article Business, Management and Accounting Intellectual Property and Patents

Nils M. Denter, Lukas Jan Aaldering, Hüseyin Caferoglu

15

citations
Kernel‐based online learning for real‐time voltage control in distribution networks
2020 IET Smart Grid article Engineering Optimal Power Flow Distribution Open access

Lisette Cupelli, Alejandro Lago Esteban, Ferdinanda Ponci, Antonello Monti

4

citations
SGD Biased towards Early Important Samples for Efficient Training
2023 conference-paper Computer Science Adversarial Robustness in Machine Learning

Alessio Quercia, Abigail Morrison, Hanno Scharr, Ira Assent

3

citations
Sinogram-based Alignment Estimation of PET Detector Blocks
2024 conference-abstract Medicine Medical Imaging Techniques and Applications

Julian Thull, Volkmar Schulz

1

citations
Focal Sampling: SGD biased towards early important samples for efficient image classification with augmentation selection
2025 Knowledge and Information Systems article Computer Science Domain Adaptation and Few-Shot Learning Open access

Alessio Quercia, Abigail Morrison, Hanno Scharr, Ira Assent

0

citations
Comparing Spectral Bias and Robustness For Two-Layer Neural Networks: SGD vs Adaptive Random Fourier Features
2024 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Aku Kammonen, Raul F. Tempone

0

citations
The pretraining domain outweighs the training objective in setting the privacy-utility trade-off of differentially private medical image analysis
2026 arXiv (Cornell University) preprint Computer Science Privacy-Preserving Technologies in Data Open access

Soroosh Tayebi Arasteh, Mina Farajiamiri, Mahshad Lotfinia, Behrus Puladi, Jonas Bienzeisler, Mohamed Alhaskir, +4 more

0

citations
Beyond Mechanics: Maximum-Likelihooddriven Pet Detector Alignment
2025 conference-abstract Medicine Medical Imaging Techniques and Applications

Julian Thull, T. Freye, Yannick Kuhl, Volkmar Schulz

0

citations
Automatic Learning of Subword Dependent Model Scales
2022 Interspeech 2022 conference-paper Computer Science Natural Language Processing Techniques Open access

Felix Meyer, Wilfried Michel, Mohammad Zeineldeen, Ralf Schlüter, Hermann Ney

0

citations
Automatic Learning of Subword Dependent Model Scales
2021 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access

Wilfried Michel, Mohammad Zeineldeen, Ralf Schlüter, Hermann Ney

0

citations
More is Less: Inducing Sparsity via Overparameterization
2021 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Hung-Hsu Chou, Johannes Maly, Holger Rauhut

1

citations
Global Stability and Step Size Robustness of RMSProp
2026 IEEE Control Systems Letters article Computer Science Distributed Control Multi-Agent Systems

Naum Dimitrieski, Maria Christine Honecker, Carsten W. Scherer, Christian Ebenbauer

1

citations
Anderson Mixing in Bures Wasserstein Space of Gaussian Measures
2026 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Vitalii Aksenov, Martin Eigel, Mathias Oster

0

citations
More is less: inducing sparsity via overparameterization
2023 Information and Inference A Journal of the IMA article Engineering Sparse and Compressive Sensing Techniques

Hung-Hsu Chou, Johannes Maly, Holger Rauhut

9

citations
Overparameterization and generalization error: weighted trigonometric interpolation
2020 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Yuege Xie, Hung-Hsu Chou, Holger Rauhut, Rachel Ward

0

citations
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction
2023 International Joint Conference on Artificial Intelligence conference-paper Computer Science Constraint Satisfaction and Optimization Open access

Jan Tönshoff, Berke Kisin, Jakob Lindner, Martin Grohe

15

citations