Xinyang Yi

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 46

Top Topics

Item Recommendation

Convex Formulation

Fundamental Limits

Recommender Systems

Top Venues

Publications

Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy
Aligning Large Language Models with Recommendation Knowledge. CoRR (2024)
Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed Huai-hsin Chi, Xinyang Yi
Leveraging LLM Reasoning Enhances Personalized Recommender Systems. ACL (Findings) (2024)
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)
Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
Improving Training Stability for Multitask Ranking Models in Recommender Systems. KDD (2023)
Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi
Improving Training Stability for Multitask Ranking Models in Recommender Systems. CoRR (2023)
Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy
Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR (2023)
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
Online Matching: A Real-time Bandit System for Large-scale Recommendations. RecSys (2023)
Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi
Online Matching: A Real-time Bandit System for Large-scale Recommendations. CoRR (2023)
Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi
Density Weighting for Multi-Interest Personalized Recommendation. CoRR (2023)
Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi
Improving Multi-Task Generalization via Regularizing Spurious Correlation. NeurIPS (2022)
Hongyi Wen, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, Ed H. Chi
Distributionally-robust Recommendations for Improving Worst-case User Experience. WWW (2022)
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 (2022)
Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen
Reward Shaping for User Satisfaction in a REINFORCE Recommender. CoRR (2022)
Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi
Improving Multi-Task Generalization via Regularizing Spurious Correlation. CoRR (2022)
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)
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)
Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed Chi, Qiaozhu Mei
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS (2021)
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)
Jyun-Yu Jiang, Tao Wu, Georgios Roumpos, Heng-Tze Cheng, Xinyang Yi, Ed Chi, Harish Ganapathy, Nitin Jindal, Pei Cao, Wei Wang
End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms. WWW (2020)
Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR (2020)
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 (2020)
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)
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 (2020)
Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi
Off-policy Learning in Two-stage Recommender Systems. WWW (2020)
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)
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 (2020)
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 (2020)
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. CoRR (2019)
Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi
Recommending what video to watch next: a multitask ranking system. RecSys (2019)
Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
Efficient Training on Very Large Corpora via Gramian Estimation. ICLR (Poster) (2019)
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)
Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson
Efficient Training on Very Large Corpora via Gramian Estimation. CoRR (2018)
Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi
Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. KDD (2018)
Yudong Chen, Xinyang Yi, Constantine Caramanis
Convex and Nonconvex Formulations for Mixed Regression With Two Components: Minimax Optimal Rates. IEEE Trans. Inf. Theory 64 (3) (2018)
Tianyang Li, Xinyang Yi, Constantine Caramanis, Pradeep Ravikumar
Minimax Gaussian Classification & Clustering. AISTATS (2017)
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization. CoRR (2016)
Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis
Fast Algorithms for Robust PCA via Gradient Descent. CoRR (2016)
Xinyang Yi, Dohyung Park, Yudong Chen, Constantine Caramanis
Fast Algorithms for Robust PCA via Gradient Descent. NIPS (2016)
Xinyang Yi, Zhaoran Wang, Zhuoran Yang, Constantine Caramanis, Han Liu
More Supervision, Less Computation: Statistical-Computational Tradeoffs in Weakly Supervised Learning. NIPS (2016)
Xinyang Yi, Constantine Caramanis, Eric Price
Binary Embedding: Fundamental Limits and Fast Algorithm. CoRR (2015)
Ye Wang, Meng Li, Xinyang Yi, Zhao Song, Michael Orshansky, Constantine Caramanis
Novel power grid reduction method based on L1 regularization. DAC (2015)
Xinyang Yi, Constantine Caramanis
Regularized EM Algorithms: A Unified Framework and Provable Statistical Guarantees. CoRR (2015)
Xinyang Yi, Constantine Caramanis
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees. NIPS (2015)
Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
Optimal linear estimation under unknown nonlinear transform. CoRR (2015)
Xinyang Yi, Constantine Caramanis, Eric Price
Binary Embedding: Fundamental Limits and Fast Algorithm. ICML (2015)
Xinyang Yi, Zhaoran Wang, Constantine Caramanis, Han Liu
Optimal Linear Estimation under Unknown Nonlinear Transform. NIPS (2015)
Yudong Chen, Xinyang Yi, Constantine Caramanis
A Convex Formulation for Mixed Regression with Two Components: Minimax Optimal Rates. COLT (2014)
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
Alternating Minimization for Mixed Linear Regression. ICML (2014)
Yudong Chen, Xinyang Yi, Constantine Caramanis
A Convex Formulation for Mixed Regression: Near Optimal Rates in the Face of Noise. CoRR (2013)