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Papers matching “training efficiency” 335

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Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey
2026 arXiv (Cornell University) preprint Computer Science Topic Modeling Open access

Vanessa Schmidt, Huy Hoang Nguyen, Cédric Jung, Shirin Salehi, Anke Schmeink

0

citations
Unifying Data, Memory, and Compute Efficiency in LLM Training: A Survey
2026 IEEE Transactions on Artificial Intelligence article Computer Science Topic Modeling

Vanessa Schmidt, Huy Hoang Nguyen, Cédric Jung, Shirin Salehi, Anke Schmeink

0

citations
Unifying Data, Memory, and Compute Efficiency in LLM training: A Survey
2026 arXiv (Cornell University) preprint Computer Science Topic Modeling Open access

Vanessa Schmidt, Huy Hoang Nguyen, Cédric Jung, Shirin Salehi, Anke Schmeink

0

citations
Generating a pixel-wise annotated training dataset to train ML algorithms for mineral identification in rock thin sections
2020 conference-abstract Computer Science Advanced Neural Network Applications Open access

Jiaxin Yu, Joyce Schmatz, Marven von Domarus, Mingze Jiang, Simon Virgo, Bastian Leibe, +1 more

0

citations
On data and knowledge transfer efficiency in deep learning
2025 RWTH Publications (RWTH Aachen) dissertation Computer Science Domain Adaptation and Few-Shot Learning Open access

Alessio Quercia

0

citations
MPX: Mixed Precision Training for JAX
2025 arXiv (Cornell University) preprint Computer Science Numerical Methods and Algorithms Open access

Alexander Gräfe, Sebastian Trimpe

0

citations
Lattice-Free Sequence Discriminative Training for Phoneme-Based Neural Transducers
2023 IEEE International Conference on Acoustics Speech and Signal Processing conference-paper Computer Science Speech Recognition and Synthesis

Zijian Győző Yang, Wei Guo Zhou, Ralf Schlüter, Hermann Ney

3

citations
Lattice-Free Sequence Discriminative Training for Phoneme-Based Neural Transducers
2022 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access

Zijian Yang, Wei Guo Zhou, Ralf Schlüter, Hermann Ney

0

citations
Post-Training Quantization for Energy Efficient Realization of Deep Neural Networks
2022 IEEE International Conference on Machine Learning and Applications (ICMLA) conference-paper Computer Science Advanced Neural Network Applications

Cecilia Latotzke, Batuhan Balim, Tobias Gemmeke

8

citations
Assessment of Simulated Data for Training Semantic Segmentation-based Perception Models in Construction
2025 Procedia Computer Science conference-paper Computer Science Domain Adaptation and Few-Shot Learning Open access

Jorge Luis Jiménez Aparicio, David Böken, Johannes Sprink, Xiaoting Wang, Jürgen Roßmann

0

citations
Post-Training Quantization for Energy Efficient Realization of Deep Neural Networks
2022 arXiv (Cornell University) preprint Computer Science Advanced Neural Network Applications Open access

Cecilia Latotzke, Batuhan Balim, Tobias Gemmeke

0

citations
SGD Biased towards Early Important Samples for Efficient Training
2023 Proceedings conference-paper Computer Science Stochastic Gradient Optimization Techniques

Alessio Quercia, Abigail Morrison, Hanno Scharr, Ira Assent

3

citations
Improving the Communication and Computation Efficiency of Split Learning for IoT Applications
2021 Globecom conference-paper Computer Science Privacy-Preserving Technologies in Data cited by 1 patent

Ahmad Ayad, Melvin Renner, Anke Schmeink

47

citations
Improving the Training Recipe for a Robust Conformer-based Hybrid Model
2022 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access

Mohammad Zeineldeen, Jingjing Xu, Ralf Schlüter, Hermann Ney

0

citations
Compression Beyond the Uncompressed: A Two-Stage Training Recipe for Soft Context Compression in RAG
2026 arXiv (Cornell University) preprint Computer Science Topic Modeling Open access

Shuyu Guo, Shuo Zhang, Zhaochun Ren

0

citations
Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer
2021 International Conference on Spoken Language Translation (IWSLT) conference-paper Computer Science Natural Language Processing Techniques Open access

Evgeniia Tokarchuk, Jan Rosendahl, Weiyue Wang, Pavel Petrushkov, Tomer Lancewicki, Shahram Khadivi, +1 more

2

citations
Efficient Sequence Training of Attention Models Using Approximative Recombination
2022 IEEE International Conference on Acoustics Speech and Signal Processing conference-paper Computer Science Speech Recognition and Synthesis

Nils-Philipp Wynands, Wilfried Michel, Jan Rosendahl, Ralf Schlüter, Hermann Ney

3

citations
Efficient Sequence Training of Attention Models using Approximative Recombination
2021 arXiv (Cornell University) preprint Computer Science Speech Recognition and Synthesis Open access

Nils-Philipp Wynands, Wilfried Michel, Jan Rosendahl, Ralf Schlüter, Hermann Ney

0

citations
Efficient Training of Neural Transducer for Speech Recognition
2022 Interspeech (USB) conference-paper Computer Science Speech Recognition and Synthesis Open access

Wei Guo Zhou, Wilfried Michel, Ralf Schlüter, Hermann Ney

15

citations
ROSAR: An Adversarial Re-Training Framework for Robust Side-Scan Sonar Object Detection
2025 conference-paper Computer Science Adversarial Robustness in Machine Learning

Martin Aubard, László Antal, Ana Maria Madureira, Luís Filipe Teixeira, Erika Ábrahám

0

citations
Iterated Population Based Training with Task-Agnostic Restarts
2025 arXiv (Cornell University) preprint Computer Science Machine Learning and Data Classification Open access

Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman

0

citations
Harnessing Manycore Processors with Distributed Memory for Accelerated Training of Sparse and Recurrent Models
2024 Proceedings of the AAAI Conference on Artificial Intelligence conference-paper Computer Science Parallel Computing and Optimization Techniques Open access

Jan Finkbeiner, Thomas Gmeinder, Mark Pupilli, Alexander Titterton, Emre Neftci

4

citations
Harnessing Manycore Processors with Distributed Memory for Accelerated Training of Sparse and Recurrent Models
2023 arXiv (Cornell University) preprint Computer Science Parallel Computing and Optimization Techniques Open access

Jan Finkbeiner, Thomas Gmeinder, Mark Pupilli, Alexander Titterton, Emre Neftci

0

citations
Bayesian Optimization via Continual Variational Last Layer Training
2024 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek

0

citations
Neural network training under semidefinite constraints
2022 Proceedings of the IEEE Conference on Decision & Control, including the Symposium on Adaptive Processes conference-paper Computer Science Stochastic Gradient Optimization Techniques cited by 1 patent

Patricia Pauli, Niklas Funcke, Dennis Gramlich, Mohamed Amine Msalmi, Frank Allgöwer

10

citations