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Steven Eliuk
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2020 – today
- 2021
- [c6]Yang Sun, Abhishek Kolagunda, Steven Eliuk, Xiaolong Wang:
Training Better Deep Neural Networks with Uncertainty Mining Net. BMVC 2021: 193 - 2020
- [c5]Xin Guo, Yu Tian, Qinghan Xue, Panos Lampropoulos, Steven Eliuk, Kenneth E. Barner, Xiaolong Wang:
Continual Learning Long Short Term Memory. EMNLP (Findings) 2020: 1817-1822
2010 – 2019
- 2019
- [c4]Qinghan Xue, Abhishek Kolagunda, Steven Eliuk, Xiaolong Wang:
AWDF: An Adaptive Weighted Deep Fusion Architecture for Multi-modality Learning. IEEE BigData 2019: 2503-2512 - 2018
- [p1]Hosub Lee
, Cameron Upright, Steven Eliuk, Alfred Kobsa:
Personalized Visual Recognition via Wearables: A First Step Toward Personal Perception Enhancement. Personal Assistants 2018: 95-112 - [i3]Christian Pinto, Yiannis Gkoufas, Andrea Reale, Seetharami Seelam, Steven Eliuk:
Hoard: A Distributed Data Caching System to Accelerate Deep Learning Training on the Cloud. CoRR abs/1812.00669 (2018) - 2016
- [c3]Steven Eliuk, Cameron Upright, Anthony Skjellum:
dMath: Linear Algebra for Scaleout GP-GPUs. HPCC/SmartCity/DSS 2016: 647-654 - [c2]Hosub Lee
, Cameron Upright, Steven Eliuk, Alfred Kobsa:
Personalized object recognition for augmenting human memory. UbiComp Adjunct 2016: 1054-1061 - [i2]Steven Eliuk, Cameron Upright, Anthony Skjellum:
dMath: A Scalable Linear Algebra and Math Library for Heterogeneous GP-GPU Architectures. CoRR abs/1604.01416 (2016) - [i1]Steven Eliuk, Cameron Upright, Hars Vardhan, Stephen Walsh, Trevor Gale:
dMath: Distributed Linear Algebra for DL. CoRR abs/1611.07819 (2016) - 2010
- [c1]Christian Andres Diaz Leon, Steven Eliuk, Helmuth Trefftz Gómez
:
Simulating soft tissues using a GPU approach of the mass-spring model. VR 2010: 261-262
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