Melih Elibol
Melih Elibol
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Cited by
Cited by
Ray: A distributed framework for emerging {AI} applications
P Moritz, R Nishihara, S Wang, A Tumanov, R Liaw, E Liang, M Elibol, ...
13th USENIX symposium on operating systems design and implementation (OSDI …, 2018
Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs
J Listgarten, M Weinstein, BP Kleinstiver, AA Sousa, JK Joung, J Crawford, ...
Nature biomedical engineering 2 (1), 38-47, 2018
Probabilistic matrix factorization for automated machine learning
N Fusi, R Sheth, M Elibol
Advances in neural information processing systems 31, 2018
Variance reduction with sparse gradients
M Elibol, L Lei, MI Jordan
arXiv preprint arXiv:2001.09623, 2020
Cross-corpora unsupervised learning of trajectories in autism spectrum disorders
HM Elibol, V Nguyen, S Linderman, M Johnson, A Hashmi, F Doshi-Velez
The Journal of Machine Learning Research 17 (1), 4597-4634, 2016
Ray: A Distributed Framework for Emerging AI Applications. arXiv e-prints, page
P Moritz, R Nishihara, S Wang, A Tumanov, R Liaw, E Liang, M Elibol, ...
arXiv preprint arXiv:1712.05889, 2017
Supervised topic models for clinical interpretability
MC Hughes, HM Elibol, T McCoy, R Perlis, F Doshi-Velez
arXiv preprint arXiv:1612.01678, 2016
NumS: Scalable Array Programming for the Cloud
HM Elibol
University of California, Berkeley, 2022
Flexible Primitives for Distributed Deep Learning in Ray
Y Bulatov, R Nishihara, P Moritz, M Elibol, I Stoica, MI Jordan
SysML Conference, 2018
Legate Sparse: Distributed Sparse Computing in Python
R Yadav, W Lee, M Elibol, M Papadakis, T Lee-Patti, M Garland, A Aiken, ...
Proceedings of the International Conference for High Performance Computing …, 2023
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