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2020 – today
- 2023
[j2]Kabir Nagrecha, Arun Kumar:
Saturn: An Optimized Data System for Multi-Large-Model Deep Learning Workloads. Proc. VLDB Endow. 17(4): 712-725 (2023)- [c5]Kabir Nagrecha
, Lingyi Liu, Pablo Delgado, Prasanna Padmanabhan:
InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models. RecSys 2023: 430-442 - [i6]Kabir Nagrecha:
Systems for Parallel and Distributed Large-Model Deep Learning Training. CoRR abs/2301.02691 (2023) - [i5]Kabir Nagrecha, Lingyi Liu, Pablo Delgado, Prasanna Padmanabhan:
InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models. CoRR abs/2308.08500 (2023) - [i4]Kabir Nagrecha, Arun Kumar:
Saturn: An Optimized Data System for Large Model Deep Learning Workloads. CoRR abs/2309.01226 (2023) - [i3]Kabir Nagrecha, Arun Kumar:
Saturn: Efficient Multi-Large-Model Deep Learning. CoRR abs/2311.02840 (2023) - 2022
- [c4]Pratyush Muthukumar, Shaurya Pathak, Kabir Nagrecha, Hirad Hosseini, Dawn Comer, Navid Amini, Jeanne Holm, Mohammad Pourhomayoun:
Multi-Pollutant Ground-level Air Pollution Prediction through Deep MeteoGCN-ConvLSTM. CSCI 2022: 26-34 - 2021
- [c3]Arun Kumar, Supun Nakandala, Yuhao Zhang, Side Li, Advitya Gemawat, Kabir Nagrecha:
Cerebro: A Layered Data Platform for Scalable Deep Learning. CIDR 2021 - [c2]Pei Wang, Kabir Nagrecha, Nuno Vasconcelos:
Gradient-Based Algorithms for Machine Teaching. CVPR 2021: 1387-1396 - [c1]Kabir Nagrecha:
Model-Parallel Model Selection for Deep Learning Systems. SIGMOD Conference 2021: 2929-2931 - [i2]Kabir Nagrecha:
Model-Parallel Model Selection for Deep Learning Systems. CoRR abs/2107.06469 (2021) - [i1]Kabir Nagrecha, Arun Kumar:
Hydra: A System for Large Multi-Model Deep Learning. CoRR abs/2110.08633 (2021) - 2020
- [j1]Supun Nakandala, Kabir Nagrecha, Arun Kumar, Yannis Papakonstantinou:
Incremental and Approximate Computations for Accelerating Deep CNN Inference. ACM Trans. Database Syst. 45(4): 16:1-16:42 (2020)
Coauthor Index
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