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Disambiguation of "Pekhimenko, Gennady"

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How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU.

, , , , , , , , , , and . CHIL, volume 174 of Proceedings of Machine Learning Research, page 169-182. PMLR, (2022)

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Gennady Uryadov

Gennady Samorodnitsky

Gennady Fedosenko

Gennady Tenin

Gennady Churakov

 

Other publications of authors with the same name

RFVP: Rollback-Free Value Prediction with Safe-to-Approximate Loads., , , , , and . ACM Trans. Archit. Code Optim., 12 (4): 62:1-62:26 (2016)Mitigating the Memory Bottleneck With Approximate Load Value Prediction., , , , , and . IEEE Des. Test, 33 (1): 32-42 (2016)Zorua: Enhancing Programming Ease, Portability, and Performance in GPUs by Decoupling Programming Models from Resource Management., , , , , , , and . CoRR, (2018)SysML: The New Frontier of Machine Learning Systems., , , , , , , , , and 56 other author(s). CoRR, (2019)LifeStream: A High-performance Stream Processing Engine for Waveform Data., , , and . CoRR, (2020)Compiler-driven performance workshop., and . CASCON, page 374-376. ACM, (2018)DietCode: Automatic Optimization for Dynamic Tensor Programs., , , , , , , , , and . MLSys, mlsys.org, (2022)Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models., , , , and . MLSys, mlsys.org, (2021)Distributed Deep Learning In Open Collaborations., , , , , , , , , and 6 other author(s). NeurIPS, page 7879-7897. (2021)Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training., , and . ISCA, page 1089-1102. IEEE, (2020)