Dhruv Choudhary

According to our database, Dhruv Choudhary authored at least 18 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Layer Compression of Deep Networks with Straight Flows.

Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Microscaling Data Formats for Deep Learning.

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

CoRR, 2023

FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models.

Geet Sethi, Pallab Bhattacharya, Dhruv Choudhary, Carole-Jean Wu, Christos Kozyrakis

CoRR, 2023

2022

RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure.

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

CoRR, 2022

Positive Unlabeled Contrastive Learning.

Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon

CoRR, 2022

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems.

Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Harmless Transfer Learning for Item Embeddings.

Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

AutoShard: Automated Embedding Table Sharding for Recommender Systems.

Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits.

Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale.

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

IEEE Micro, 2021

Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters.

Yuzhen Huang, Xiaohan Wei, Xing Wang, Jiyan Yang, Bor-Yiing Su, Shivam Bharuka, Dhruv Choudhary, Zewei Jiang, Hai Zheng, Jack Langman

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism.

Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems.

Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020

Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism.

Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney

CoRR, 2020

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data.

Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal

CoRR, 2020

2017

On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data.

Dhruv Choudhary, Arun Kejariwal, Francois Orsini

CoRR, 2017

2011

Regulating Locality vs. Parallelism Tradeoffs in Multiple Memory Controller Environments.

Syed Minhaj Hassan, Dhruv Choudhary, Mitchelle Rasquinha, Sudhakar Yalamanchili

Proceedings of the 2011 International Conference on Parallel Architectures and Compilation Techniques, 2011

2010

An energy efficient cache design using spin torque transfer (STT) RAM.

Mitchelle Rasquinha, Dhruv Choudhary, Subho Chatterjee, Saibal Mukhopadhyay, Sudhakar Yalamanchili

Proceedings of the 2010 International Symposium on Low Power Electronics and Design, 2010