Jiyan Yang

According to our database, Jiyan Yang authored at least 33 papers between 2014 and 2024.

Collaborative distances:

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

2024

CubicML: Automated ML for Large ML Systems Co-design with ML Prediction of Performance.

Wei Wen, Quanyu Zhu, Weiwei Chu, Wen-Yen Chen, Jiyan Yang

CoRR, 2024

AutoML for Large Capacity Modeling of Meta's Ranking Systems.

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

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale.

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

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

2023

AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations.

Danwei Li, Zhengyu Zhang, Siyang Yuan, Mingze Gao, Weilin Zhang, Chaofei Yang, Xi Liu, Jiyan Yang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking.

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

Proceedings of the Workshop on Data Mining for Online Advertising (AdKDD 2023) co-located with the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023

2022

DHEN: A Deep and Hierarchical Ensemble Network for Large-Scale Click-Through Rate Prediction.

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

CoRR, 2022

Software-hardware co-design for fast and scalable training of deep learning recommendation models.

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, 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, Ajit Mathews, Lin Qiao, Mikhail Smelyanskiy, Bill Jia, Vijay Rao

Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022

2021

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

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

CoRR, 2021

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

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

Proceedings of the Fourth Conference on Machine Learning and Systems, 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

Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems.

Antonio A. Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou

Proceedings of the IEEE International Symposium on Information Theory, 2021

2020

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

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

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

Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems.

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

CoRR, 2020

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

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

CoRR, 2020

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction.

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

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems.

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

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

Post-Training 4-bit Quantization on Embedding Tables.

Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen

CoRR, 2019

A Study of BFLOAT16 for Deep Learning Training.

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

CoRR, 2019

2017

Weighted SGD for $\ell_p$ Regression with Randomized Preconditioning.

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

J. Mach. Learn. Res., 2017

2016

Distributed Online Modified Greedy Algorithm for Networked Storage Operation Under Uncertainty.

Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal

IEEE Trans. Smart Grid, 2016

Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments.

Jiyan Yang, Xiangrui Meng, Michael W. Mahoney

Proc. IEEE, 2016

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels.

Haim Avron, Vikas Sindhwani, Jiyan Yang, Michael W. Mahoney

J. Mach. Learn. Res., 2016

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.

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

CoRR, 2016

Weighted SGD for <i>ℓ_p</i> Regression with Randomized Preconditioning.

Jiyan Yang, Yinlam Chow, Christopher Ré, Michael W. Mahoney

Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, 2016

Feature-distributed sparse regression: a screen-and-clean approach.

Jiyan Yang, Michael W. Mahoney, Michael A. Saunders, Yuekai Sun

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Sub-sampled Newton Methods with Non-uniform Sampling.

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

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark.

Alex Gittens, Jey Kottalam, Jiyan Yang, Michael F. Ringenburg, Jatin Chhugani, Evan Racah, Mohitdeep Singh, Yushu Yao, Curt Fischer, Oliver Rübel, Benjamin P. Bowen, Norman G. Lewis, Michael W. Mahoney, Venkat Krishnamurthy, Prabhat

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies.

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

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Tensor machines for learning target-specific polynomial features.

Jiyan Yang, Alex Gittens

CoRR, 2015

2014

Quantile Regression for Large-Scale Applications.

Jiyan Yang, Xiangrui Meng, Michael W. Mahoney

SIAM J. Sci. Comput., 2014

Modeling and online control of generalized energy storage networks.

Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal

Proceedings of the Fifth International Conference on Future Energy Systems, 2014

Random Laplace Feature Maps for Semigroup Kernels on Histograms.

Jiyan Yang, Vikas Sindhwani, Quanfu Fan, Haim Avron, Michael W. Mahoney

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014