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Dhruv Choudhary
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2020 – today
- 2024
- [c11]Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu:
Layer Compression of Deep Networks with Straight Flows. AAAI 2024: 12181-12189 - [i14]Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort:
SpinQuant: LLM quantization with learned rotations. CoRR abs/2405.16406 (2024) - [i13]Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, Arun Rao, Aston Zhang, Aurélien Rodriguez, Austen Gregerson, Ava Spataru, Baptiste Rozière, Bethany Biron, Binh Tang, Bobbie Chern, Charlotte Caucheteux, Chaya Nayak, Chloe Bi, Chris Marra, Chris McConnell, Christian Keller, Christophe Touret, Chunyang Wu, Corinne Wong, Cristian Canton Ferrer, Cyrus Nikolaidis, Damien Allonsius, Daniel Song, Danielle Pintz, Danny Livshits, David Esiobu, Dhruv Choudhary, Dhruv Mahajan, Diego Garcia-Olano, Diego Perino, Dieuwke Hupkes, Egor Lakomkin, Ehab AlBadawy, Elina Lobanova, Emily Dinan, Eric Michael Smith, Filip Radenovic, Frank Zhang, Gabriel Synnaeve, Gabrielle Lee, Georgia Lewis Anderson, Graeme Nail, Grégoire Mialon, Guan Pang, Guillem Cucurell, Hailey Nguyen, Hannah Korevaar, Hu Xu, Hugo Touvron, Iliyan Zarov, Imanol Arrieta Ibarra, Isabel M. Kloumann, Ishan Misra, Ivan Evtimov, Jade Copet, Jaewon Lee, Jan Geffert, Jana Vranes, Jason Park, Jay Mahadeokar, Jeet Shah, Jelmer van der Linde, Jennifer Billock, Jenny Hong, Jenya Lee, Jeremy Fu, Jianfeng Chi, Jianyu Huang, Jiawen Liu, Jie Wang, Jiecao Yu, Joanna Bitton, Joe Spisak, Jongsoo Park, Joseph Rocca, Joshua Johnstun, Joshua Saxe, Junteng Jia, Kalyan Vasuden Alwala, Kartikeya Upasani, Kate Plawiak, Ke Li, Kenneth Heafield, Kevin Stone, et al.:
The Llama 3 Herd of Models. CoRR abs/2407.21783 (2024) - 2023
- [c10]Mark Zhao, Dhruv Choudhary, Devashish Tyagi, Ajay Somani, Max Kaplan, Sung-Han Lin, Sarunya Pumma, Jongsoo Park, Aarti Basant, Niket Agarwal, Carole-Jean Wu, Christos Kozyrakis:
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. MLSys 2023 - [i12]Geet Sethi, Pallab Bhattacharya, Dhruv Choudhary, Carole-Jean Wu, Christos Kozyrakis:
FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models. CoRR abs/2301.02959 (2023) - [i11]Bita Darvish Rouhani, Ritchie Zhao, Ankit More, Mathew Hall, Alireza Khodamoradi, Summer Deng, Dhruv Choudhary, Marius Cornea, Eric Dellinger, Kristof Denolf, Dusan Stosic, Venmugil Elango, Maximilian Golub, Alexander Heinecke, Phil James-Roxby, Dharmesh Jani, Gaurav Kolhe, Martin Langhammer, Ada Li, Levi Melnick, Maral Mesmakhosroshahi, Andres Rodriguez, Michael Schulte, Rasoul Shafipour, Lei Shao, Michael Y. Siu, Pradeep Dubey, Paulius Micikevicius, Maxim Naumov, Colin Verilli, Ralph Wittig, Doug Burger, Eric S. Chung:
Microscaling Data Formats for Deep Learning. CoRR abs/2310.10537 (2023) - 2022
- [c9]Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan:
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR 2022 - [c8]Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. KDD 2022: 4461-4471 - [c7]Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal:
Harmless Transfer Learning for Item Embeddings. NAACL-HLT (Findings) 2022: 504-516 - [c6]Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu:
Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. UAI 2022: 2256-2266 - [i10]Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon:
Positive Unlabeled Contrastive Learning. CoRR abs/2206.01206 (2022) - [i9]Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu:
AutoShard: Automated Embedding Table Sharding for Recommender Systems. CoRR abs/2208.06399 (2022) - [i8]Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu:
Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems. CoRR abs/2209.01143 (2022) - [i7]Mark Zhao, Dhruv Choudhary, Devashish Tyagi, Ajay Somani, Max Kaplan, Sung-Han Lin, Sarunya Pumma, Jongsoo Park, Aarti Basant, Niket Agarwal, Carole-Jean Wu, Christos Kozyrakis:
RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. CoRR abs/2211.05239 (2022) - 2021
- [j1]Zhaoxia Deng
, Jongsoo Park
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. IEEE Micro 41(5): 93-100 (2021) - [c5]Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal:
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. ICMLA 2021: 1421-1428 - [c4]Vipul Gupta
Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. KDD 2021: 2928-2936 - [c3]Yuzhen Huang, Xiaohan Wei, Xing Wang, Jiyan Yang, Bor-Yiing Su, Shivam Bharuka, Dhruv Choudhary, Zewei Jiang, Hai Zheng, Jack Langman:
Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters. KDD 2021: 3050-3058 - [i6]Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal:
Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. CoRR abs/2105.01064 (2021) - [i5]Zhaoxia Deng, Jongsoo Park, Ping Tak Peter Tang, Haixin Liu, Jie Yang, Hector Yuen, Jianyu Huang, Daya Shanker Khudia, Xiaohan Wei, Ellie Wen, Dhruv Choudhary, Raghuraman Krishnamoorthi, Carole-Jean Wu, Nadathur Satish, Changkyu Kim, Maxim Naumov, Sam Naghshineh, Mikhail Smelyanskiy:
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. CoRR abs/2105.12676 (2021) - [i4]Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan:
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. CoRR abs/2110.04844 (2021) - 2020
- [i3]Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal:
Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. CoRR abs/2010.08655 (2020) - [i2]Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney:
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. CoRR abs/2010.08899 (2020)
2010 – 2019
- 2017
- [i1]Dhruv Choudhary, Arun Kejariwal, Francois Orsini:
On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data. CoRR abs/1710.04735 (2017) - 2011
- [c2]Syed Minhaj Hassan, Dhruv Choudhary, Mitchelle Rasquinha, Sudhakar Yalamanchili:
Regulating Locality vs. Parallelism Tradeoffs in Multiple Memory Controller Environments. PACT 2011: 187-188 - 2010
- [c1]Mitchelle Rasquinha, Dhruv Choudhary, Subho Chatterjee, Saibal Mukhopadhyay, Sudhakar Yalamanchili:
An energy efficient cache design using spin torque transfer (STT) RAM. ISLPED 2010: 389-394
Coauthor Index
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