Incremental and Approximate Computations for Accelerating Deep CNN Inference. - Supun Nakandala; Kabir Nagrecha; Arun Kumar 001; Yannis Papakonstantinou (ACM Trans. Database Syst., 2020)

Cerebro: A Layered Data Platform for Scalable Deep Learning. - Arun Kumar 001; Supun Nakandala; Yuhao Zhang; Side Li; Advitya Gemawat; Kabir Nagrecha (CIDR, 2021)

Gradient-Based Algorithms for Machine Teaching. - Pei Wang; Kabir Nagrecha; Nuno Vasconcelos (CVPR, 2021)

Model-Parallel Model Selection for Deep Learning Systems. - Kabir Nagrecha (SIGMOD Conference, 2021)

Hydra: A System for Large Multi-Model Deep Learning. - Kabir Nagrecha; Arun Kumar 001 (CoRR, 2021)

Multi-Pollutant Ground-level Air Pollution Prediction through Deep MeteoGCN-ConvLSTM. - Pratyush Muthukumar; Shaurya Pathak; Kabir Nagrecha; Hirad Hosseini; Dawn Comer; Navid Amini; Jeanne Holm; Mohammad Pourhomayoun (CSCI, 2022)

InTune: Reinforcement Learning-based Data Pipeline Optimization for Deep Recommendation Models. - Kabir Nagrecha; Lingyi Liu; Pablo Delgado; Prasanna Padmanabhan (RecSys, 2023)

Systems for Parallel and Distributed Large-Model Deep Learning Training. - Kabir Nagrecha (CoRR, 2023)

Saturn: An Optimized Data System for Large Model Deep Learning Workloads. - Kabir Nagrecha; Arun Kumar 001 (CoRR, 2023)

Saturn: Efficient Multi-Large-Model Deep Learning. - Kabir Nagrecha; Arun Kumar 001 (CoRR, 2023)

Saturn: An Optimized Data System for Multi-Large-Model Deep Learning Workloads. - Kabir Nagrecha; Arun Kumar 001 (Proc. VLDB Endow., 2023)

Orchestration Systems to Support Deep Learning at Scale - Kabir Nagrecha (2024)