1 code implementation • EMNLP 2021 • Paras Jain, Ajay Jain, Tianjun Zhang, Pieter Abbeel, Joseph E. Gonzalez, Ion Stoica
Recent work learns contextual representations of source code by reconstructing tokens from their context.
Ranked #1 on Method name prediction on CodeSearchNet
1 code implementation • 15 Jul 2022 • Shishir G. Patil, Paras Jain, Prabal Dutta, Ion Stoica, Joseph E. Gonzalez
We demonstrate that it is possible to fine-tune both ResNet-18 and BERT within the memory constraints of a Cortex-M class embedded device while outperforming current edge training methods in energy efficiency.
2 code implementations • 7 Oct 2019 • Paras Jain, Ajay Jain, Aniruddha Nrusimha, Amir Gholami, Pieter Abbeel, Kurt Keutzer, Ion Stoica, Joseph E. Gonzalez
We formalize the problem of trading-off DNN training time and memory requirements as the tensor rematerialization optimization problem, a generalization of prior checkpointing strategies.
1 code implementation • NeurIPS 2021 • Zhanghao Wu, Paras Jain, Matthew A. Wright, Azalia Mirhoseini, Joseph E. Gonzalez, Ion Stoica
Inspired by recent computer vision results that find position-invariant attention performant in learning long-range relationships, our method, which we call GraphTrans, applies a permutation-invariant Transformer module after a standard GNN module.
1 code implementation • NeurIPS 2021 • Jeffrey Ichnowski, Paras Jain, Bartolomeo Stellato, Goran Banjac, Michael Luo, Francesco Borrelli, Joseph E. Gonzalez, Ion Stoica, Ken Goldberg
First-order methods for quadratic optimization such as OSQP are widely used for large-scale machine learning and embedded optimal control, where many related problems must be rapidly solved.
1 code implementation • Findings (EMNLP) 2021 • Yu Gai, Paras Jain, Wendi Zhang, Joseph E. Gonzalez, Dawn Song, Ion Stoica
Grounding enables the model to retain syntax information from the input in thereby significantly improving generalization over complex inputs.
no code implementations • 17 Nov 2018 • Paden Tomasello, Sammy Sidhu, Anting Shen, Matthew W. Moskewicz, Nobie Redmon, Gayatri Joshi, Romi Phadte, Paras Jain, Forrest Iandola
Recently, autonomous vehicles have created a demand for depth information, which is often obtained using hardware sensors such as Light detection and ranging (LIDAR).
no code implementations • 28 Jan 2019 • Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica
Current trends in Machine Learning~(ML) inference on hardware accelerated devices (e. g., GPUs, TPUs) point to alarmingly low utilization.