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Yingxue Zhou
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2020 – today
- 2024
- [c12]Yancheng Wang, Ziyan Jiang, Zheng Chen, Fan Yang, Yingxue Zhou, Eunah Cho, Xing Fan, Yanbin Lu, Xiaojiang Huang, Yingzhen Yang:
RecMind: Large Language Model Powered Agent For Recommendation. NAACL-HLT (Findings) 2024: 4351-4364 - [i10]Arindam Banerjee, Qiaobo Li, Yingxue Zhou:
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees. CoRR abs/2406.07712 (2024) - 2023
- [c11]Yingxue Zhou, Jie Hao, Mukund Rungta, Yang Liu, Eunah Cho, Xing Fan, Yanbin Lu, Vishal Thanvantri Vasudevan, Kellen Gillespie, Zeynab Raeesy:
Unified Contextual Query Rewriting. ACL (industry) 2023: 608-615 - [c10]Zhongkai Sun, Yingxue Zhou, Jie Hao, Xing Fan, Yanbin Lu, Chengyuan Ma, Wei Shen, Chenlei Guo:
Improving Contextual Query Rewrite for Conversational AI Agents through User-preference Feedback Learning. EMNLP (Industry Track) 2023: 432-439 - [i9]Yancheng Wang, Ziyan Jiang, Zheng Chen, Fan Yang, Yingxue Zhou, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, Yingzhen Yang:
RecMind: Large Language Model Powered Agent For Recommendation. CoRR abs/2308.14296 (2023) - 2022
- [c9]Xianyu Meng, Liangli Ma, Yingxue Zhou:
Research on Locking Suspect by Using Mathematical Model. ICCDE 2022: 105-110 - [c8]Arindam Banerjee, Tiancong Chen, Xinyan Li, Yingxue Zhou:
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics. ICML 2022: 1412-1449 - [c7]Xianyu Meng, Liangli Ma, Yingxue Zhou:
Analysis and Example Implementation of Data Visualization Technology. ICMVA 2022: 56-60 - [c6]Yingxue Zhou, Xinyan Li, Arindam Banerjee:
Noisy Truncated SGD: Optimization and Generalization. SDM 2022: 468-476 - [i8]Arindam Banerjee, Tiancong Chen, Xinyan Li, Yingxue Zhou:
Stability Based Generalization Bounds for Exponential Family Langevin Dynamics. CoRR abs/2201.03064 (2022) - 2021
- [c5]Yingxue Zhou, Steven Wu
, Arindam Banerjee:
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification. ICLR 2021 - [i7]Yingxue Zhou, Xinyan Li, Arindam Banerjee:
Noisy Truncated SGD: Optimization and Generalization. CoRR abs/2103.00075 (2021) - 2020
- [c4]Yingxue Zhou, Belhal Karimi, Jinxing Yu, Zhiqiang Xu, Ping Li:
Towards Better Generalization of Adaptive Gradient Methods. NeurIPS 2020 - [c3]Xinyan Li, Qilong Gu, Yingxue Zhou, Tiancong Chen, Arindam Banerjee:
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization. SDM 2020: 190-198 - [i6]Arindam Banerjee, Tiancong Chen, Yingxue Zhou:
De-randomized PAC-Bayes Margin Bounds: Applications to Non-convex and Non-smooth Predictors. CoRR abs/2002.09956 (2020) - [i5]Yingxue Zhou, Xiangyi Chen, Mingyi Hong, Zhiwei Steven Wu, Arindam Banerjee:
Private Stochastic Non-Convex Optimization: Adaptive Algorithms and Tighter Generalization Bounds. CoRR abs/2006.13501 (2020) - [i4]Yingxue Zhou, Zhiwei Steven Wu, Arindam Banerjee:
Bypassing the Ambient Dimension: Private SGD with Gradient Subspace Identification. CoRR abs/2007.03813 (2020)
2010 – 2019
- 2019
- [i3]Xinyan Li, Qilong Gu, Yingxue Zhou, Tiancong Chen, Arindam Banerjee:
Hessian based analysis of SGD for Deep Nets: Dynamics and Generalization. CoRR abs/1907.10732 (2019) - 2018
- [c2]Yingxue Zhou, Sheng Chen, Arindam Banerjee:
Stable Gradient Descent. UAI 2018: 766-775 - 2016
- [j1]Pan Zhou, Yingxue Zhou, Dapeng Wu
Differentially Private Online Learning for Cloud-Based Video Recommendation With Multimedia Big Data in Social Networks. IEEE Trans. Multim. 18(6): 1217-1229 (2016) - [c1]Chencheng Li, Pan Zhou, Yingxue Zhou, Kaigui Bian, Tao Jiang, Susanto Rahardja:
Distributed private online learning for social big data computing over data center networks. ICC 2016: 1-6 - [i2]Chencheng Li, Pan Zhou, Yingxue Zhou, Kaigui Bian, Tao Jiang, Susanto Rahardja:
Distributed Private Online Learning for Social Big Data Computing over Data Center Networks. CoRR abs/1602.06489 (2016) - 2015
- [i1]Pan Zhou, Yingxue Zhou, Dapeng Wu, Hai Jin:
Differentially Private Online Learning for Video Recommendation with Social Big Data over Media Cloud. CoRR abs/1509.00181 (2015)
Coauthor Index
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