Dhruv Choudhary

27 papers A* 6A 2B 1C 1Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Accelerating Transformer Inference and Training with 2:4 Activation Sparsity. CoRR Daniel Haziza, Timothy Chou, Dhruv Choudhary, Luca Wehrstedt, Francisco Massa, Jiecao Yu, Geonhwa Jeong, Supriya Rao, Patrick Labatut, Jesse Cai
2025	A*	`conf`	SpinQuant: LLM Quantization with Learned Rotations. ICLR Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort
2024	A*	`conf`	Layer Compression of Deep Networks with Straight Flows. AAAI Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu
2024	J	`jnl`	SpinQuant: LLM quantization with learned rotations. CoRR Zechun Liu, Changsheng Zhao, Igor Fedorov, Bilge Soran, Dhruv Choudhary, Raghuraman Krishnamoorthi, Vikas Chandra, Yuandong Tian, Tijmen Blankevoort
2023	J	`jnl`	FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models. CoRR Geet Sethi, Pallab Bhattacharya, Dhruv Choudhary, Carole-Jean Wu, Christos Kozyrakis
2023	J	`jnl`	Microscaling Data Formats for Deep Learning. CoRR 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
2023	—	`conf`	RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. MLSys 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
2022	A*	`conf`	AutoShard: Automated Embedding Table Sharding for Recommender Systems. KDD Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu
2022	J	`jnl`	AutoShard: Automated Embedding Table Sharding for Recommender Systems. CoRR Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu
2022	A*	`conf`	Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
2022	J	`jnl`	Future Gradient Descent for Adapting the Temporal Shifting Data Distribution in Online Recommendation Systems. CoRR Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
2022	A	`conf`	Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. UAI Mao Ye, Ruichen Jiang, Haoxiang Wang, Dhruv Choudhary, Xiaocong Du, Bhargav Bhushanam, Aryan Mokhtari, Arun Kejariwal, Qiang Liu
2022	—	`conf`	Harmless Transfer Learning for Item Embeddings. NAACL-HLT (Findings) Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal
2022	J	`jnl`	Positive Unlabeled Contrastive Learning. CoRR Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon
2022	J	`jnl`	RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure. CoRR 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
2021	C	`conf`	Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. ICMLA Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
2021	J	`jnl`	Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems. CoRR Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal
2021	J	`jnl`	Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. CoRR Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
2021	A*	`conf`	Hierarchical Training: Scaling Deep Recommendation Models on Large CPU Clusters. KDD Yuzhen Huang, Xiaohan Wei, Xing Wang, Jiyan Yang, Bor-Yiing Su, Shivam Bharuka, Dhruv Choudhary, Zewei Jiang, Hai Zheng, Jack Langman
2021	J	`jnl`	Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. CoRR 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
2021	J	`jnl`	Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale. IEEE Micro 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
2021	A*	`conf`	Training Recommender Systems at Scale: Communication-Efficient Model and Data Parallelism. KDD Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney
2020	J	`jnl`	Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. CoRR Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, ZeLiang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal
2020	J	`jnl`	Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism. CoRR Vipul Gupta, Dhruv Choudhary, Ping Tak Peter Tang, Xiaohan Wei, Xing Wang, Yuzhen Huang, Arun Kejariwal, Kannan Ramchandran, Michael W. Mahoney
2017	J	`jnl`	On the Runtime-Efficacy Trade-off of Anomaly Detection Techniques for Real-Time Streaming Data. CoRR Dhruv Choudhary, Arun Kejariwal, Francois Orsini
2011	B	`conf`	Regulating Locality vs. Parallelism Tradeoffs in Multiple Memory Controller Environments. PACT Syed Minhaj Hassan, Dhruv Choudhary, Mitchelle Rasquinha, Sudhakar Yalamanchili
2010	A	`conf`	An energy efficient cache design using spin torque transfer (STT) RAM. ISLPED Mitchelle Rasquinha, Dhruv Choudhary, Subho Chatterjee, Saibal Mukhopadhyay, Sudhakar Yalamanchili