Cedric Renggli
Cedric Renggli
Verified email at - Homepage
Cited by
Cited by
The convergence of sparsified gradient methods
D Alistarh, T Hoefler, M Johansson, N Konstantinov, S Khirirat, C Renggli
Advances in Neural Information Processing Systems 31, 2018
SparCML: High-performance sparse communication for machine learning
C Renggli, S Ashkboos, M Aghagolzadeh, D Alistarh, T Hoefler
Proceedings of the International Conference for High Performance Computing …, 2019
A data quality-driven view of mlops
C Renggli, L Rimanic, NM Gürel, B Karlaš, W Wu, C Zhang
arXiv preprint arXiv:2102.07750, 2021
Distributed learning over unreliable networks
C Yu, H Tang, C Renggli, S Kassing, A Singla, D Alistarh, C Zhang, J Liu
International Conference on Machine Learning, 7202-7212, 2019
Scalable transfer learning with expert models
J Puigcerver, C Riquelme, B Mustafa, C Renggli, AS Pinto, S Gelly, ...
arXiv preprint arXiv:2009.13239, 2020
Continuous integration of machine learning models with ease. ml/ci: Towards a rigorous yet practical treatment
C Renggli, B Karlaš, B Ding, F Liu, K Schawinski, W Wu, C Zhang
Proceedings of Machine Learning and Systems 1, 322-333, 2019
Learning to merge tokens in vision transformers
C Renggli, AS Pinto, N Houlsby, B Mustafa, J Puigcerver, C Riquelme
arXiv preprint arXiv:2202.12015, 2022
Building continuous integration services for machine learning
B Karlaš, M Interlandi, C Renggli, W Wu, C Zhang, ...
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
Decoding EEG brain activity for multi-modal natural language processing
N Hollenstein, C Renggli, B Glaus, M Barrett, M Troendle, N Langer, ...
Frontiers in Human Neuroscience 15, 659410, 2021
Ease. ml: a lifecycle management system for machine learning
L Aguilar Melgar, D Dao, S Gan, NM Gürel, N Hollenstein, J Jiang, ...
Proceedings of the Annual Conference on Innovative Data Systems Research …, 2021
Which model to transfer? finding the needle in the growing haystack
C Renggli, AS Pinto, L Rimanic, J Puigcerver, C Riquelme, C Zhang, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Ease. ml/ci and ease. ml/meter in action: Towards data management for statistical generalization
C Renggli, FA Hubis, B Karlaš, K Schawinski, W Wu, C Zhang
Proceedings of the VLDB Endowment 12 (12), 1962-1965, 2019
On convergence of nearest neighbor classifiers over feature transformations
L Rimanic, C Renggli, B Li, C Zhang
Advances in Neural Information Processing Systems 33, 12521-12532, 2020
In-database machine learning with corgipile: Stochastic gradient descent without full data shuffle
L Xu, S Qiu, B Yuan, J Jiang, C Renggli, S Gan, K Kara, G Li, J Liu, W Wu, ...
Proceedings of the 2022 International Conference on Management of Data, 1286 …, 2022
Lossy image compression with recurrent neural networks: from human perceived visual quality to classification accuracy
M Weber, C Renggli, H Grabner, C Zhang
arXiv preprint arXiv:1910.03472, 2019
Co-design hardware and algorithm for vector search
W Jiang, S Li, Y Zhu, J de Fine Licht, Z He, R Shi, C Renggli, S Zhang, ...
Proceedings of the International Conference for High Performance Computing …, 2023
Ease. ML: A lifecycle management system for MLDev and MLOps
L Aguilar, D Dao, S Gan, NM Gurel, N Hollenstein, J Jiang, B Karlas, ...
Proc. of Innovative Data Systems Research, 2021
Speeding up percolator
JT Halloran, H Zhang, K Kara, C Renggli, M The, C Zhang, DM Rocke, ...
Journal of proteome research 18 (9), 3353-3359, 2019
Evaluating Bayes error estimators on real-world datasets with FeeBee
C Renggli, L Rimanic, N Hollenstein, C Zhang
arXiv preprint arXiv:2108.13034, 2021
Observer dependent lossy image compression
M Weber, C Renggli, H Grabner, C Zhang
Pattern Recognition: 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen …, 2021
The system can't perform the operation now. Try again later.
Articles 1–20