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2020 – today
- 2024
[i11]Santiago Castro, Amir Ziai, Avneesh Saluja, Zhuoning Yuan, Rada Mihalcea:
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models. CoRR abs/2402.15021 (2024)- 2023
- [j3]Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang:
Memory-Based Optimization Methods for Model-Agnostic Meta-Learning and Personalized Federated Learning. J. Mach. Learn. Res. 24: 145:1-145:46 (2023) - [j2]Zhishuai Guo, Yan Yan
, Zhuoning Yuan, Tianbao Yang:
Fast Objective & Duality Gap Convergence for Non-Convex Strongly-Concave Min-Max Problems with PL Condition. J. Mach. Learn. Res. 24: 148:1-148:63 (2023) - [c15]Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang:
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. ICML 2023: 28389-28421 - [c14]Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang:
LibAUC: A Deep Learning Library for X-Risk Optimization. KDD 2023: 5487-5499 - [i10]Zi-Hao Qiu, Quanqi Hu, Zhuoning Yuan, Denny Zhou, Lijun Zhang, Tianbao Yang:
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization. CoRR abs/2305.11965 (2023) - [i9]Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang:
LibAUC: A Deep Learning Library for X-Risk Optimization. CoRR abs/2306.03065 (2023) - 2022
- [c13]Zhuoning Yuan, Zhishuai Guo, Nitesh V. Chawla, Tianbao Yang:
Compositional Training for End-to-End Deep AUC Maximization. ICLR 2022 - [c12]Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang:
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. ICML 2022: 25760-25782 - [i8]Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang:
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance. CoRR abs/2202.12387 (2022) - 2021
- [c11]Zhuoning Yuan, Yan Yan, Milan Sonka, Tianbao Yang:
Large-scale Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification. ICCV 2021: 3020-3029 - [c10]Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang:
Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity. ICML 2021: 12219-12229 - [i7]Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang:
Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity. CoRR abs/2102.04635 (2021) - [i6]Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang:
Memory-based Optimization Methods for Model-Agnostic Meta-Learning. CoRR abs/2106.04911 (2021) - 2020
- [c9]Zhuoning Yuan, Zhishuai Guo, Xiaotian Yu, Xiaoyu Wang, Tianbao Yang:
Accelerating Deep Learning with Millions of Classes. ECCV (23) 2020: 711-726 - [c8]Yichen Ding, Xun Zhou, Han Bao, Yanhua Li, Cara Hamann, Steven Spears, Zhuoning Yuan:
Cycling-Net: A Deep Learning Approach to Predicting Cyclist Behaviors from Geo-Referenced Egocentric Video Data. SIGSPATIAL/GIS 2020: 337-346 - [c7]Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang:
Stochastic AUC Maximization with Deep Neural Networks. ICLR 2020 - [c6]Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang:
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks. ICML 2020: 3864-3874 - [i5]Zhishuai Guo, Mingrui Liu, Zhuoning Yuan, Li Shen, Wei Liu, Tianbao Yang:
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks. CoRR abs/2005.02426 (2020) - [i4]Zhishuai Guo, Zhuoning Yuan, Yan Yan, Tianbao Yang:
Fast Objective and Duality Gap Convergence for Non-convex Strongly-concave Min-max Problems. CoRR abs/2006.06889 (2020) - [i3]Zhuoning Yuan, Yan Yan, Milan Sonka, Tianbao Yang:
Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification. CoRR abs/2012.03173 (2020)
2010 – 2019
- 2019
- [j1]Xing Fang, Zhuoning Yuan:
Performance enhancing techniques for deep learning models in time series forecasting. Eng. Appl. Artif. Intell. 85: 533-542 (2019) - [c5]Zaiyi Chen, Zhuoning Yuan, Jinfeng Yi, Bowen Zhou, Enhong Chen, Tianbao Yang:
Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions. ICLR (Poster) 2019 - [c4]Yi Xu, Zhuoning Yuan, Sen Yang, Rong Jin, Tianbao Yang:
On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization. IJCAI 2019: 4003-4009 - [c3]Zhuoning Yuan, Yan Yan, Rong Jin, Tianbao Yang:
Stagewise Training Accelerates Convergence of Testing Error Over SGD. NeurIPS 2019: 2604-2614 - [i2]Mingrui Liu, Zhuoning Yuan, Yiming Ying, Tianbao Yang:
Stochastic AUC Maximization with Deep Neural Networks. CoRR abs/1908.10831 (2019) - 2018
- [c2]Zhuoning Yuan, Xun Zhou, Tianbao Yang:
Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data. KDD 2018: 984-992 - [i1]Tianbao Yang, Yan Yan, Zhuoning Yuan, Rong Jin:
Why Does Stagewise Training Accelerate Convergence of Testing Error Over SGD? CoRR abs/1812.03934 (2018) - 2015
- [c1]Mohd Anwar, Zhuoning Yuan:
Linking Obesity and Tweets. ICSH 2015: 254-266
Coauthor Index
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last updated on 2024-10-07 22:24 CEST by the dblp team
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