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CoDiet publications

CoDiet partners are committed to publishing their findings in openly accessible scientific papers.

The publications listed below will grow over the course of the project and all are freely accessible and acknowledge CoDiet’s funding bodies, the European Commission and UKRI.

Kim, Kim, Sohn, Beck, Rei, Kim, Simpson, Posma, Lain, Sung, Kang (2023) Advancing phenotype named entity recognition and normalization for dysmorphology physical examination reports, Proceedings of the BioCreative VIII Challenge and Workshop: Curation and Evaluation in the era of Generative Models. https://zenodo.org/doi/10.5281/zenodo.10104803 

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Zhou and Mareček (2023) Learning of Linear Dynamical Systems as a Noncommutative Polynomial Optimization Problem, IEEE Transactions on Automatic Control. https://ieeexplore.ieee.org/document/10244076

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Tsenos, Peri and Kalogeraki (2023) Energy Efficient Scheduling for Serverless Systems. IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS).  https://ieeexplore.ieee.org/document/10336044

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Peri, Tsenos and Kalogeraki (2023) Orchestrating the Execution of Serverless Functions in Hybrid Clouds, 2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS). https://ieeexplore.ieee.org/document/10336026

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Tomaras, Tsenos and Kalogeraki (2023) Prediction-driven resource provisioning for serverless container runtimes, IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS). https://ieeexplore.ieee.org/document/10336036

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Wang, Vijayaraghava, Beck and Posma. (2024) Vocabulary Matters: An Annotation Pipeline and Four Deep Learning Algorithms for Enzyme Named Entity Recognition. Journal of Proteome Research. https://pubs.acs.org/doi/10.1021/acs.jproteome.3c00367

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Kozdoba, Perets, Mannor. (2023) Unnormalized Density Estimation with Root Sobolev Norm Regularization. 15th Annual Workshop on Optimization for Machine Learning. https://openreview.net/forum?id=PDxpsZmyrr

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Kozdoba, Perets, Mannor. (2023) Learning Hidden Markov Models When the Locations of Missing Observations are Unknown, Arkiv. https://arxiv.org/abs/2203.06527

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Gu, Vahidian, Kungurtsev, Wang, Jiang, You, Chen. (2024) Efficient Dataset Distillation via Minimax Diffusion, Arkiv. https://arxiv.org/abs/2311.15529

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Tomaras, Tsenos, Kalogeraki and Gunopulos. (2024) TIMBER: On supporting data pipelines in Mobile Cloud Environments, 25th IEEE International Conference on Mobile Data Management (MDM). https://doi.org/10.1109/MDM61037.2024.00032

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Kozdoba, Perets, Mannor (2023) Unnormalized Density Estimation with Root Sobolev Norm Regularization, NeurIPS 2023 Second Table Representation Learning Workshop. https://openreview.net/forum?id=ejfKPO9aw0

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Kozdoba, Perets, Mannor. (2024) Sobolev Space Regularised Pre Density Models. Proceedings of the 41st International Conference on Machine Learning in Proceedings of Machine Learning Research. https://proceedings.mlr.press/v235/kozdoba24a.html

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