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\n  \n 2022\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n A Framework for Synthesizing Low-Power Approximate Inference Accelerators.\n \n \n \n\n\n \n Paras Jain; Safeen Huda; Martin Maas; Joseph E. Gonzalez; Ion Stoica; and Azalia Mirhoseini.\n\n\n \n\n\n\n In DATE 2022, 2022. \n \n\n\n\n
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@inproceedings{jain2022framework,\n  title     = {A Framework for Synthesizing Low-Power Approximate Inference Accelerators},\n  author    = {Jain, Paras and Huda, Safeen and Maas, Martin and Gonzalez, Joseph E. and Stoica, Ion and Mirhoseini, Azalia},\n  booktitle = {DATE 2022},\n  year      = {2022}\n}\n\n
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\n \n\n \n \n \n \n \n Systems and methods for training machine models with augmented data.\n \n \n \n\n\n \n Matthew John Cooper; Paras Jagdish Jain; and Harsimran Singh Sidhu.\n\n\n \n\n\n\n April 7 2022.\n US Patent App. 17/644,308\n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@misc{cooper2022systems,\n  title  = {Systems and methods for training machine models with augmented data},\n  author = {Cooper, Matthew John and Jain, Paras Jagdish and Sidhu, Harsimran Singh},\n  year   = {2022},\n  month  = apr # {~7},\n  note   = {US Patent App. 17/644,308}\n}
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\n  \n 2021\n \n \n (7)\n \n \n
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\n \n\n \n \n \n \n \n Multi-channel sensor simulation for autonomous control systems.\n \n \n \n\n\n \n Forrest Nelson Iandola; Donald Benton MacMillen; Anting Shen; Harsimran Singh Sidhu; Daniel Paden Tomasello; Rohan Nandkumar Phadte; and Paras Jagdish Jain.\n\n\n \n\n\n\n October 26 2021.\n US Patent 11,157,014\n\n\n\n
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@misc{iandola2021multi,\n  title  = {Multi-channel sensor simulation for autonomous control systems},\n  author = {Iandola, Forrest Nelson and MacMillen, Donald Benton and Shen, Anting and Sidhu, Harsimran Singh and Tomasello, Daniel Paden and Phadte, Rohan Nandkumar and Jain, Paras Jagdish},\n  year   = {2021},\n  month  = oct # {~26},\n  note   = {US Patent 11,157,014}\n}\n\n
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\n \n\n \n \n \n \n \n Systems and methods for training machine models with augmented data.\n \n \n \n\n\n \n Matthew John Cooper; Paras Jagdish Jain; and Harsimran Singh Sidhu.\n\n\n \n\n\n\n December 21 2021.\n US Patent 11,205,093\n\n\n\n
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@misc{cooper2021systems,\n  title  = {Systems and methods for training machine models with augmented data},\n  author = {Cooper, Matthew John and Jain, Paras Jagdish and Sidhu, Harsimran Singh},\n  year   = {2021},\n  month  = dec # {~21},\n  note   = {US Patent 11,205,093}\n}\n\n
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\n \n\n \n \n \n \n \n Contrastive Code Representation Learning.\n \n \n \n\n\n \n Paras Jain; Ajay Jain; Tianjun Zhang; Pieter Abbeel; Joseph E Gonzalez; and Ion Stoica.\n\n\n \n\n\n\n EMNLP 2021. 2021.\n \n\n\n\n
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@article{jain2021contrastive,\n  title   = {Contrastive Code Representation Learning},\n  author  = {Jain, Paras and Jain, Ajay and Zhang, Tianjun and Abbeel, Pieter and Gonzalez, Joseph E and Stoica, Ion},\n  journal = {EMNLP 2021},\n  year    = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Accelerating Quadratic Optimization with Reinforcement Learning.\n \n \n \n\n\n \n Jeffrey Ichnowski; Paras Jain; Bartolomeo Stellato; Goran Banjac; Michael Luo; Francesco Borrelli; Joseph E Gonzalez; Ion Stoica; and Ken Goldberg.\n\n\n \n\n\n\n NeurIPS 2021. 2021.\n \n\n\n\n
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@article{ichnowski2021accelerating,\n  title   = {Accelerating Quadratic Optimization with Reinforcement Learning},\n  author  = {Ichnowski, Jeffrey and Jain, Paras and Stellato, Bartolomeo and Banjac, Goran and Luo, Michael and Borrelli, Francesco and Gonzalez, Joseph E and Stoica, Ion and Goldberg, Ken},\n  journal = {NeurIPS 2021},\n  year    = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Synthesizing Low-Power Approximate Hardware with Large-Scale Search.\n \n \n \n\n\n \n Paras Jain; Safeen Huda; Martin Maas; Joseph Gonzalez; Ion Stoica; and Azalia Mirhoseini.\n\n\n \n\n\n\n In MLArchSys at the International Symposium on Computer Architecture 2021, 2021. \n \n\n\n\n
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@inproceedings{jain2021synthesizing,\n  title     = {Synthesizing Low-Power Approximate Hardware with Large-Scale Search},\n  author    = {Jain, Paras and Huda, Safeen and Maas, Martin and Gonzalez, Joseph and Stoica, Ion and Mirhoseini, Azalia},\n  booktitle = {MLArchSys at the International Symposium on Computer Architecture 2021},\n  year      = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Grounded Graph Decoding improves Compositional Generalization in Question Answering.\n \n \n \n\n\n \n Yu Gai; Paras Jain; Wendi Zhang; Joseph E. Gonzalez; Ion Stoica; and Dawn Song.\n\n\n \n\n\n\n In Findings of EMNLP 2021, 2021. \n \n\n\n\n
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@inproceedings{gai2021grounded,\n  title     = {Grounded Graph Decoding improves Compositional Generalization in Question Answering},\n  author    = {Gai, Yu and Jain, Paras and Zhang, Wendi and Gonzalez, Joseph E. and Stoica, Ion and Song, Dawn},\n  booktitle = {Findings of EMNLP 2021},\n  year      = {2021}\n}\n\n
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\n \n\n \n \n \n \n \n Representing Long-Range Context for Graph Neural Networks with Global Attention.\n \n \n \n\n\n \n Zhanghao Wu; Paras Jain; Matthew Wright; Azalia Mirhoseini; Joseph E. Gonzalez; and Ion Stoica.\n\n\n \n\n\n\n In NeurIPS 2021, 2021. \n \n\n\n\n
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@inproceedings{wu2021representing,\n  title     = {Representing Long-Range Context for Graph Neural Networks with Global Attention},\n  author    = {Wu, Zhanghao and Jain, Paras and Wright, Matthew and Mirhoseini, Azalia and Gonzalez, Joseph E. and Stoica, Ion},\n  booktitle = {NeurIPS 2021},\n  year      = {2021}\n}\n\n
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\n  \n 2020\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n Data synthesis for autonomous control systems.\n \n \n \n\n\n \n Forrest Nelson Iandola; Donald Benton MacMillen; Anting Shen; Harsimran Singh Sidhu; and Paras Jagdish Jain.\n\n\n \n\n\n\n June 9 2020.\n US Patent 10,678,244\n\n\n\n
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@misc{iandola2020data,\n  title  = {Data synthesis for autonomous control systems},\n  author = {Iandola, Forrest Nelson and MacMillen, Donald Benton and Shen, Anting and Sidhu, Harsimran Singh and Jain, Paras Jagdish},\n  year   = {2020},\n  month  = jun # {~9},\n  note   = {US Patent 10,678,244}\n}\n\n
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\n \n\n \n \n \n \n \n Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization.\n \n \n \n\n\n \n Paras Jain; Ajay Jain; Aniruddha Nrusimha; Amir Gholami; Pieter Abbeel; Kurt Keutzer; Ion Stoica; and Joseph E. Gonzalez.\n\n\n \n\n\n\n In Proceedings of Machine Learning and Systems 2020, pages 497–511, 2020. \n \n\n\n\n
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@inproceedings{jain2020checkmate,\n  title     = {Checkmate: Breaking the Memory Wall with Optimal Tensor Rematerialization},\n  author    = {Jain, Paras and Jain, Ajay and Nrusimha, Aniruddha and Gholami, Amir and Abbeel, Pieter and Keutzer, Kurt and Stoica, Ion and Gonzalez, Joseph E.},\n  booktitle = {Proceedings of Machine Learning and Systems 2020},\n  pages     = {497--511},\n  year      = {2020}\n}\n\n
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\n \n\n \n \n \n \n \n Optimizing neural network structures for embedded systems.\n \n \n \n\n\n \n Harsimran Singh Sidhu; Paras Jagdish Jain; Daniel Paden Tomasello; and Forrest Nelson Iandola.\n\n\n \n\n\n\n January 30 2020.\n US Patent App. 16/522,411\n\n\n\n
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@misc{sidhu2020optimizing,\n  title  = {Optimizing neural network structures for embedded systems},\n  author = {Sidhu, Harsimran Singh and Jain, Paras Jagdish and Tomasello, Daniel Paden and Iandola, Forrest Nelson},\n  year   = {2020},\n  month  = jan # {~30},\n  note   = {US Patent App. 16/522,411}\n}\n\n
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\n  \n 2019\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n DSCnet: Replicating lidar point clouds with deep sensor cloning.\n \n \n \n\n\n \n Paden Tomasello; Sammy Sidhu; Anting Shen; Matthew W Moskewicz; Nobie Redmon; Gayatri Joshi; Romi Phadte; Paras Jain; and Forrest Iandola.\n\n\n \n\n\n\n In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pages 0–0, 2019. \n \n\n\n\n
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@inproceedings{tomasello2019dscnet,\n  title     = {DSCnet: Replicating lidar point clouds with deep sensor cloning},\n  author    = {Tomasello, Paden and Sidhu, Sammy and Shen, Anting and Moskewicz, Matthew W and Redmon, Nobie and Joshi, Gayatri and Phadte, Romi and Jain, Paras and Iandola, Forrest},\n  booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops},\n  pages     = {0--0},\n  year      = {2019}\n}\n\n
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\n \n\n \n \n \n \n \n The OoO VLIW JIT compiler for GPU inference.\n \n \n \n\n\n \n Paras Jain; Xiangxi Mo; Ajay Jain; Alexey Tumanov; Joseph E Gonzalez; and Ion Stoica.\n\n\n \n\n\n\n arXiv preprint arXiv:1901.10008. 2019.\n \n\n\n\n
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@article{jain2019ooo,\n  title   = {The OoO VLIW JIT compiler for GPU inference},\n  author  = {Jain, Paras and Mo, Xiangxi and Jain, Ajay and Tumanov, Alexey and Gonzalez, Joseph E and Stoica, Ion},\n  journal = {arXiv preprint arXiv:1901.10008},\n  year    = {2019}\n}\n\n
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\n \n\n \n \n \n \n \n Revec: program rejuvenation through revectorization.\n \n \n \n\n\n \n Charith Mendis; Ajay Jain; Paras Jain; and Saman Amarasinghe.\n\n\n \n\n\n\n In Proceedings of the 28th International Conference on Compiler Construction, pages 29–41, 2019. \n \n\n\n\n
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@inproceedings{mendis2019revec,\n  title     = {Revec: program rejuvenation through revectorization},\n  author    = {Mendis, Charith and Jain, Ajay and Jain, Paras and Amarasinghe, Saman},\n  booktitle = {Proceedings of the 28th International Conference on Compiler Construction},\n  pages     = {29--41},\n  year      = {2019}\n}\n\n
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\n  \n 2018\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Dynamic Space-Time Scheduling for GPU Inference.\n \n \n \n\n\n \n Paras Jain; Xiangxi Mo; Ajay Jain; Harikaran Subbaraj; Rehan Durrani; Alexey Tumanov; Joseph Gonzalez; and Ion Stoica.\n\n\n \n\n\n\n In LearningSys Workshop at Neural Information Processing Systems 2018, 2018. \n \n\n\n\n
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@inproceedings{jain2018dynamic,\n  title     = {Dynamic Space-Time Scheduling for GPU Inference},\n  author    = {Jain, Paras and Mo, Xiangxi and Jain, Ajay and Subbaraj, Harikaran and Durrani, Rehan and Tumanov, Alexey and Gonzalez, Joseph and Stoica, Ion},\n  booktitle = {LearningSys Workshop at Neural Information Processing Systems 2018},\n  year      = {2018}\n}\n\n
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\n \n\n \n \n \n \n \n Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets.\n \n \n \n\n\n \n Paras Jain; Chirag Tailor; Sam Ford; Liexiao Ding; Michael Phillips; Fang Liu; Nagi Gebraeel; and Duen Horng Chau.\n\n\n \n\n\n\n In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pages 1078–1082, 2017. IEEE\n \n\n\n\n
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@inproceedings{jain2017scalable,\n  title        = {Scalable Architecture for Anomaly Detection and Visualization in Power Generating Assets},\n  author       = {Jain, Paras and Tailor, Chirag and Ford, Sam and Ding, Liexiao and Phillips, Michael and Liu, Fang and Gebraeel, Nagi and Chau, Duen Horng},\n  booktitle    = {2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)},\n  pages        = {1078--1082},\n  year         = {2017},\n  organization = {IEEE}\n}\n\n
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\n \n\n \n \n \n \n \n Spotting Suspicious Reviews via (Quasi-) clique Extraction.\n \n \n \n\n\n \n Paras Jain; Shang-Tse Chen; Mozhgan Azimpourkivi; Duen Horng Chau; and Bogdan Carbunar.\n\n\n \n\n\n\n In IEEE Security and Privacy 2015 extended abstract, 2015. \n \n\n\n\n
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@inproceedings{jain2015spotting,\n  title     = {Spotting Suspicious Reviews via (Quasi-) clique Extraction},\n  author    = {Jain, Paras and Chen, Shang-Tse and Azimpourkivi, Mozhgan and Chau, Duen Horng and Carbunar, Bogdan},\n  booktitle = {IEEE Security and Privacy 2015 extended abstract},\n  year      = {2015}\n}\n\n
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