Publications

BLENDER: Blended Text Embeddings and Diffusion Residuals for Intra-Class Image Synthesis in Deep Metric Learning
Jan Niklas Kolf, Ozan Tezcan, Justin Theiss, Hyung Jun Kim, Wentao Bao, Bhargav Bhushanam, Khushi Gupta, Arun Kejariwal, Naser Damer, Fadi Boutros
CoRR abs/2601.20246 (2026)

Layer Compression of Deep Networks with Straight Flows
Chengyue Gong, Xiaocong Du, Bhargav Bhushanam, Lemeng Wu, Xingchao Liu, Dhruv Choudhary, Arun Kejariwal, Qiang Liu
AAAI 2024

Characterization of Data Compression in Datacenters
Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna
ISPASS 2023
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models
Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu
MLSys 2023
HHVM Performance Optimization for Large Scale Web Services
Yuhao Li, Abhishek Gupta, Alex Yang, Peinan Chen, Joey Pinto, Brian Karrer, Mayank Pundir, Maximilian Balandat, Arun Kejariwal, Benjamin C. Lee
ICPE 2023

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs
Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
HiPC 2022
Understanding Data Compression in Warehouse-Scale Datacenter Services
Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna
ISPASS 2022
Building a Performance Model for Deep Learning Recommendation Model Training on GPUs
Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens
ISPASS 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
KDD 2022
Harmless Transfer Learning for Item Embeddings
Chengyue Gong, Xiaocong Du, Dhruv Choudhary, Bhargav Bhushanam, Qiang Liu, Arun Kejariwal
NAACL-HLT (Findings) 2022
DreamShard: Generalizable Embedding Table Placement for Recommender Systems
Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu
NeurIPS 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
UAI 2022

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
ICMLA 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
KDD 2021