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High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models


Apr 15, 2021
Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Andrew Tulloch, Srinivas Sridharan, Xing Liu, Mustafa Ozdal, Jade Nie, Jongsoo Park, Liang Luo, Jie Amy Yang, Leon Gao, Dmytro Ivchenko, Aarti Basant, Yuxi Hu, Jiyan Yang, Ehsan K. Ardestani, Xiaodong Wang, Rakesh Komuravelli, Ching-Hsiang Chu, Serhat Yilmaz, Huayu Li, Jiyuan Qian, Zhuobo Feng, Yinbin Ma, Junjie Yang, Ellie Wen, Hong Li, Lin Yang, Chonglin Sun, Whitney Zhao, Dimitry Melts, Krishna Dhulipala, KR Kishore, Tyler Graf, Assaf Eisenman, Kiran Kumar Matam, Adi Gangidi, Guoqiang Jerry Chen, Manoj Krishnan, Avinash Nayak, Krishnakumar Nair, Bharath Muthiah, Mahmoud khorashadi, Pallab Bhattacharya, Petr Lapukhov, Maxim Naumov, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao


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CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery


Nov 05, 2020
Kiwan Maeng, Shivam Bharuka, Isabel Gao, Mark C. Jeffrey, Vikram Saraph, Bor-Yiing Su, Caroline Trippel, Jiyan Yang, Mike Rabbat, Brandon Lucia, Carole-Jean Wu


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


Oct 21, 2020
Mao Ye, Dhruv Choudhary, Jiecao Yu, Ellie Wen, Zeliang Chen, Jiyan Yang, Jongsoo Park, Qiang Liu, Arun Kejariwal


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Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction


Jun 29, 2020
Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu


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ShadowSync: Performing Synchronization in the Background for Highly Scalable Distributed Training


Mar 07, 2020
Qinqing Zheng, Bor-Yiing Su, Jiyan Yang, Alisson Azzolini, Qiang Wu, Ou Jin, Shri Karandikar, Hagay Lupesko, Liang Xiong, Eric Zhou


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Post-Training 4-bit Quantization on Embedding Tables


Nov 05, 2019
Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen

* Accepted in [email protected]'19 (http://learningsys.org/neurips19/

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Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems


Sep 25, 2019
Antonio Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou


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Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems


Sep 04, 2019
Hao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang

* 20 pages, 11 figures, 4 tables 

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A Study of BFLOAT16 for Deep Learning Training


Jun 13, 2019
Dhiraj Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey


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Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning


Jul 10, 2017
Jiyan Yang, Yin-Lam Chow, Christopher Ré, Michael W. Mahoney

* A conference version of this paper appears under the same title in Proceedings of ACM-SIAM Symposium on Discrete Algorithms, Arlington, VA, 2016 

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Sub-sampled Newton Methods with Non-uniform Sampling


Jul 05, 2016
Peng Xu, Jiyan Yang, Farbod Roosta-Khorasani, Christopher Ré, Michael W. Mahoney

* minor fix on v1 

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Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels


Aug 09, 2015
Haim Avron, Vikas Sindhwani, Jiyan Yang, Michael Mahoney

* A short version of this paper has been presented in ICML 2014 

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Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments


Jul 27, 2015
Jiyan Yang, Xiangrui Meng, Michael W. Mahoney


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Tensor machines for learning target-specific polynomial features


Apr 07, 2015
Jiyan Yang, Alex Gittens

* 19 pages, 4 color figures, 2 tables. Submitted to ECML 2015 

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Quantile Regression for Large-scale Applications


Jan 07, 2014
Jiyan Yang, Xiangrui Meng, Michael W. Mahoney

* 35 pages; long version of a paper appearing in the 2013 ICML. Version to appear in the SIAM Journal on Scientific Computing 

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