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Papers matching “gradient-based learning” 14

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Understanding transfer learning and gradient-based meta-learning techniques
2023 Machine Learning article Computer Science Domain Adaptation and Few-Shot Learning Open access cited by 1 patent

Mike Huisman, Aske Plaat, Jan N. van Rijn

12

citations
Understanding Transfer Learning and Gradient-Based Meta-Learning Techniques
2023 arXiv (Cornell University) preprint Computer Science Domain Adaptation and Few-Shot Learning Open access

Mike Huisman, Aske Plaat, Jan N. van Rijn

0

citations
Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression?
2023 Genetic and Evolutionary Computation Conference (GECCO) conference-paper Computer Science Evolutionary Algorithms and Applications Open access

Joe Harrison, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman

8

citations
A Truly Sparse and General Implementation of Gradient-Based Synaptic Plasticity
2025 conference-paper Computer Science Neural Networks and Applications

Jamie Lohofl, Florian Assmuth, Emre Neftci

0

citations
A Truly Sparse and General Implementation of Gradient-Based Synaptic Plasticity
2025 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Jamie Lohoff, Florian Assmuth, Emre Neftci

0

citations
Subspace Adaptation Prior for Few-Shot Learning
2023 Machine Learning article Computer Science Domain Adaptation and Few-Shot Learning Open access

Mike Huisman, Aske Plaat, Jan N. van Rijn

4

citations
Subspace Adaptation Prior for Few-Shot Learning
2023 arXiv (Cornell University) preprint Computer Science Domain Adaptation and Few-Shot Learning Open access

Mike Huisman, Aske Plaat, Jan N. van Rijn

0

citations
Data-Driven Qubit Characterization and Optimal Control using Deep Learning
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Paul Surrey, Julian D. Teske, Tobias Hangleiter, Hendrik Bluhm, Pascal Cerfontaine

0

citations
Data-Driven Qubit Characterization and Optimal Control using Deep Learning
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Paul Surrey, Julian D. Teske, Tobias Hangleiter, Hendrik Bluhm, Pascal Cerfontaine

0

citations
Cautious optimism for deep parameterized quantum circuits
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Marie Kempkes, Elies Gil-Fuster, Carlos Bravo-Prieto, Aroosa Ijaz, Alissa Wilms, Jens Eisert, +2 more

0

citations
Symbolic Pauli Propagation for Gradient-Enabled Pre-Training of Quantum Circuits
2025 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

0

citations
Solving Deep Reinforcement Learning Tasks with Evolution Strategies and Linear Policy Networks
2026 ACM Transactions on Evolutionary Learning and Optimization article Computer Science Reinforcement Learning in Robotics Open access

Annie Wong, Jacob de Nobel, Thomas Bäck, Aske Plaat, Anna V. Kononova

0

citations
Exploring the Phase Diagram of the quantum one-dimensional ANNNI model
2024 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

María Cea, Michele Grossi, E. Rico, Luca Tagliacozzo, Sofia Vallecorsa

1

citations
Coreset Selection With K-CREST: Evaluation of a Sustainable Approach on Remote Sensing Data
2026 IEEE Access article Computer Science Machine Learning and Data Classification Open access

Samy Hashim, Ehsan Zandi, Rocco Sedona, Shirin Salehi, Anke Schmeink, Morris Riedel, +1 more

0

citations

14 results