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ORCIDZhiyuan Cheng 0002
Person information
- affiliation: Google
Other persons with the same name
- Zhiyuan Cheng — disambiguation page
- Zhiyuan Cheng 0001 — Texas A&M University, College Station, TX, USA
- Zhiyuan Cheng 0003 — University of Electronic Science and Technology of China, Chengdu, China
- Zhiyuan Cheng 0004 — Beihang University, State Key Lab. of Software Development Environment, Beijing, China
- Zhiyuan Cheng 0005 — Communication University of China, College of Information Engineering, Beijing, China
- Zhiyuan Cheng 0006 — Nanjing University of Posts and Telecommunications, School of Computer, China
- Zhiyuan Cheng 0007 — Zhejiang University, College of Information Science and Electronic Engineering, Hangzhou, China
- Zhiyuan Cheng 0008 — Huazhong University of Science and Technology, Wuhan, China
- Zhiyuan Cheng 0009 — Zhejiang University, School of Micro-Nanoelectronics, Provincial Key Lab of Micro-Nano Electronic and Smart System, Hangzhou, China
- Zhiyuan Cheng 0010
![[0000-0001-7280-6079]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-7280-6079")
— Purdue University, West Lafayette, IN, USA - Zhiyuan Cheng 0011 — Chinese Academy of Science, Xi'an Institute of Optics and Precision Mechnics, China
- Zhiyuan Cheng 0012 — Anhui University, School of Computer Science and Technology, Hefei, China
- Zhiyuan Cheng 0013 — Shanghai University of Electronic Power, School of Electric Power Engineering, China (and 1 more)
- Zhiyuan Cheng 0014 — iFLYTEK Co., Ltd., Hefei, China
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Conference and Workshop Papers
- 2024
[c18]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, James Caverlee, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Improving Data Efficiency for Recommenders and LLMs. RecSys 2024: 790-792- [c17]Yin Zhang, Ruoxi Wang, Xiang Li, Tiansheng Yao, Andrew Evdokimov, Jonathan Valverde, Yuan Gao, Jerry Zhang, Evan Ettinger, Ed H. Chi, Derek Zhiyuan Cheng:
Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders. RecSys 2024: 829-831 - 2023
- [c16]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD 2023: 5608-5617 - [c15]Derek Zhiyuan Cheng, Dhaval Patel, Linsey Pang, Sameep Mehta, Kexin Xie, Ed H. Chi, Wei Liu, Nitesh V. Chawla, James Bailey:
Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. KDD 2023: 5853-5854 - [c14]Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS 2023 - [c13]Derek Zhiyuan Cheng, Ruoxi Wang, Wang-Cheng Kang, Benjamin Coleman, Yin Zhang, Jianmo Ni, Jonathan Valverde, Lichan Hong, Ed H. Chi:
Efficient Data Representation Learning in Google-scale Systems. RecSys 2023: 267-271 - [c12]Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng:
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. SIGIR 2023: 2062-2066 - 2022
- [c11]Ning Ma, Mustafa Ispir, Yuan Li, Yongpeng Yang, Zhe Chen, Derek Zhiyuan Cheng, Lan Nie, Kishor Barman:
An Online Multi-task Learning Framework for Google Feed Ads Auction Models. KDD 2022: 3477-3485 - 2021
- [c10]Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, Evan Ettinger:
Self-supervised Learning for Large-scale Item Recommendations. CIKM 2021: 4321-4330 - [c9]Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Learning to Embed Categorical Features without Embedding Tables for Recommendation. KDD 2021: 840-850 - [c8]Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui:
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. WSDM 2021: 76-84 - [c7]Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi:
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems. WWW 2021: 1785-1797 - [c6]Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi:
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. WWW 2021: 2220-2231 - 2020
- [c5]Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, Ed H. Chi:
Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. WWW (Companion Volume) 2020: 441-447 - [c4]Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi:
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. WWW (Companion Volume) 2020: 562-566 - 2019
- [c3]Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi:
Sampling-bias-corrected neural modeling for large corpus item recommendations. RecSys 2019: 269-277 - 2017
- [c2]Alex Beutel, Ed Huai-hsin Chi, Zhiyuan Cheng, Hubert Pham, John R. Anderson:
Beyond Globally Optimal: Focused Learning for Improved Recommendations. WWW 2017: 203-212 - 2015
- [c1]Zhe Zhao, Zhiyuan Cheng, Lichan Hong, Ed Huai-hsin Chi:
Improving User Topic Interest Profiles by Behavior Factorization. WWW 2015: 1406-1416
Informal and Other Publications
- 2024
- [i12]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng:
How to Train Data-Efficient LLMs. CoRR abs/2402.09668 (2024) - 2023
- [i11]Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. CoRR abs/2305.06474 (2023) - [i10]Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR abs/2305.12102 (2023) - [i9]Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng:
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. CoRR abs/2305.17386 (2023) - [i8]Noveen Sachdeva, Zexue He, Wang-Cheng Kang, Jianmo Ni, Derek Zhiyuan Cheng, Julian J. McAuley:
Farzi Data: Autoregressive Data Distillation. CoRR abs/2310.09983 (2023) - 2022
- [i7]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR abs/2210.14309 (2022) - 2020
- [i6]Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi:
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. CoRR abs/2002.08530 (2020) - [i5]Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger:
Self-supervised Learning for Deep Models in Recommendations. CoRR abs/2007.12865 (2020) - [i4]Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui:
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. CoRR abs/2008.07032 (2020) - [i3]Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi:
DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. CoRR abs/2008.13535 (2020) - [i2]Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Deep Hash Embedding for Large-Vocab Categorical Feature Representations. CoRR abs/2010.10784 (2020) - [i1]Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi:
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. CoRR abs/2010.15982 (2020)
Coauthor Index
aka: Ed Huai-hsin Chi
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