default search action
Jiyan Yang
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [c19]Wei Wen
, Kuang-Hung Liu
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale. WWW (Companion Volume) 2024: 73-82 - [c18]Hang Yin
AutoML for Large Capacity Modeling of Meta's Ranking Systems. WWW (Companion Volume) 2024: 374-382 - [i21]Wei Wen, Quanyu Zhu, Weiwei Chu, Wen-Yen Chen, Jiyan Yang:
CubicML: Automated ML for Large ML Systems Co-design with ML Prediction of Performance. CoRR abs/2409.04585 (2024) - 2023
- [c17]Xuewei Wang, Qiang Jin, Shengyu Huang, Min Zhang, Xi Liu, Zhengli Zhao, Yukun Chen, Zhengyu Zhang, Jiyan Yang, Ellie Wen, Sagar Chordia, Wenlin Chen, Qin Huang:
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking. AdKDD@KDD 2023 - [c16]Danwei Li
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations. KDD 2023: 4370-4379 - [i20]Danwei Li, Zhengyu Zhang, Siyang Yuan, Mingze Gao, Weilin Zhang, Chaofei Yang, Xi Liu, Jiyan Yang:
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations. CoRR abs/2304.04959 (2023) - [i19]Xuewei Wang, Qiang Jin, Shengyu Huang, Min Zhang, Xi Liu, Zhengli Zhao, Yukun Chen, Zhengyu Zhang, Jiyan Yang, Ellie Wen, Sagar Chordia, Wenlin Chen, Qin Huang:
Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking. CoRR abs/2307.11096 (2023) - [i18]Hang Yin, Kuang-Hung Liu, Mengying Sun, Yuxin Chen, Buyun Zhang, Jiang Liu, Vivek Sehgal, Rudresh Rajnikant Panchal, Eugen Hotaj, Xi Liu, Daifeng Guo, Jamey Zhang, Zhou Wang, Shali Jiang, Huayu Li, Zhengxing Chen, Wen-Yen Chen, Jiyan Yang, Wei Wen:
AutoML for Large Capacity Modeling of Meta's Ranking Systems. CoRR abs/2311.07870 (2023) - [i17]Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen:
Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale. CoRR abs/2311.08430 (2023) - 2022
- [c15]Dheevatsa Mudigere, Yuchen Hao, Jianyu Huang, Zhihao Jia, 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
Software-hardware co-design for fast and scalable training of deep learning recommendation models. ISCA 2022: 993-1011 - [i16]Buyun Zhang, Liang Luo, Xi Liu, Jay Li, Zeliang Chen, Weilin Zhang, Xiaohan Wei, Yuchen Hao, Michael Tsang, Wenjun Wang, Yang Liu, Huayu Li, Yasmine Badr, Jongsoo Park, Jiyan Yang, Dheevatsa Mudigere, Ellie Wen:
DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction. CoRR abs/2203.11014 (2022) - 2021
- [c14]Antonio A. Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou:
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems. ISIT 2021: 2786-2791 - [c13]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 - [c12]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:
Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. MLSys 2021 - [i15]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, K. R. 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:
High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models. CoRR abs/2104.05158 (2021) - 2020
- [c11]Hao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang:
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems. KDD 2020: 165-175 - [c10]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. KDD 2020: 945-955 - [i14]Qinqing Zheng, Bor-Yiing Su, Jiyan Yang, Alisson G. Azzolini, Qiang Wu, Ou Jin, Shri Karandikar, Hagay Lupesko, Liang Xiong, Eric Zhou:
ShadowSync: Performing Synchronization in the Background for Highly Scalable Distributed Training. CoRR abs/2003.03477 (2020) - [i13]Maxim Naumov, John Kim, Dheevatsa Mudigere, Srinivas Sridharan, Xiaodong Wang, Whitney Zhao, Serhat Yilmaz, Changkyu Kim, Hector Yuen, Mustafa Ozdal, Krishnakumar Nair, Isabel Gao, Bor-Yiing Su, Jiyan Yang, Mikhail Smelyanskiy:
Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems. CoRR abs/2003.09518 (2020) - [i12]Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. CoRR abs/2007.06434 (2020) - [i11]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) - [i10]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:
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. CoRR abs/2011.02999 (2020)
2010 – 2019
- 2019
- [i9]Dhiraj D. 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:
A Study of BFLOAT16 for Deep Learning Training. CoRR abs/1905.12322 (2019) - [i8]Hao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang:
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems. CoRR abs/1909.02107 (2019) - [i7]Antonio Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou:
Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems. CoRR abs/1909.11810 (2019) - [i6]Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen:
Post-Training 4-bit Quantization on Embedding Tables. CoRR abs/1911.02079 (2019) - 2017
- [j5]Jiyan Yang, Yin-Lam Chow, Christopher Ré, Michael W. Mahoney:
Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning. J. Mach. Learn. Res. 18: 211:1-211:43 (2017) - 2016
- [j4]Haim Avron
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. J. Mach. Learn. Res. 17: 120:1-120:38 (2016) - [j3]Jiyan Yang, Xiangrui Meng, Michael W. Mahoney:
Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments. Proc. IEEE 104(1): 58-92 (2016) - [j2]Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal:
Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty. IEEE Trans. Smart Grid 7(2): 1106-1118 (2016) - [c9]Alex Gittens, Aditya Devarakonda
Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. IEEE BigData 2016: 204-213 - [c8]Alex Gittens, Jey Kottalam, Jiyan Yang, Michael F. Ringenburg
A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark. IPDPS Workshops 2016: 1403-1412 - [c7]Jiyan Yang, Michael W. Mahoney, Michael A. Saunders, Yuekai Sun:
Feature-distributed sparse regression: a screen-and-clean approach. NIPS 2016: 2712-2720 - [c6]Peng Xu, Jiyan Yang, Farbod Roosta-Khorasani, Christopher Ré, Michael W. Mahoney:
Sub-sampled Newton Methods with Non-uniform Sampling. NIPS 2016: 3000-3008 - [c5]Jiyan Yang, Yinlam Chow, Christopher Ré, Michael W. Mahoney:
Weighted SGD for ℓp Regression with Randomized Preconditioning. SODA 2016: 558-569 - [i5]Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat:
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. CoRR abs/1607.01335 (2016) - 2015
- [i4]Jiyan Yang, Xiangrui Meng, Michael W. Mahoney:
Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments. CoRR abs/1502.03032 (2015) - [i3]Jiyan Yang, Alex Gittens:
Tensor machines for learning target-specific polynomial features. CoRR abs/1504.01697 (2015) - 2014
- [j1]Jiyan Yang, Xiangrui Meng, Michael W. Mahoney:
Quantile Regression for Large-Scale Applications. SIAM J. Sci. Comput. 36(5) (2014) - [c4]Jiyan Yang, Vikas Sindhwani, Quanfu Fan, Haim Avron, Michael W. Mahoney:
Random Laplace Feature Maps for Semigroup Kernels on Histograms. CVPR 2014: 971-978 - [c3]Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal:
Modeling and online control of generalized energy storage networks. e-Energy 2014: 27-38 - [c2]Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney:
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. ICML 2014: 485-493 - [i2]Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael W. Mahoney:
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels. CoRR abs/1412.8293 (2014) - 2013
- [c1]Jiyan Yang, Xiangrui Meng, Michael W. Mahoney:
Quantile Regression for Large-scale Applications. ICML (3) 2013: 881-887 - [i1]Jiyan Yang, Xiangrui Meng, Michael W. Mahoney:
Quantile Regression for Large-scale Applications. CoRR abs/1305.0087 (2013)
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-05 21:59 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: