Linjun Zhang

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 74

Top Topics

Calibration Method

Demand Forecasting

Invariant Representations

Top Venues

Publications

Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
Can AI Be as Creative as Humans? CoRR (2024)
Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao
Calibrated Self-Rewarding Vision Language Models. CoRR (2024)
Lujing Zhang, Aaron Roth, Linjun Zhang
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks. CoRR (2024)
Qichuan Yin, Junzhou Huang, Huaxiu Yao, Linjun Zhang
Distribution-Free Fair Federated Learning with Small Samples. CoRR (2024)
Tianxi Cai, Feiqing Huang, Ryumei Nakada, Linjun Zhang, Doudou Zhou
Contrastive Learning on Multimodal Analysis of Electronic Health Records. CoRR (2024)
Huiying Zhong, Zhun Deng, Weijie J. Su, Zhiwei Steven Wu, Linjun Zhang
Provable Multi-Party Reinforcement Learning with Diverse Human Feedback. CoRR (2024)
Xintao Xia, Linjun Zhang, Zhanrui Cai
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm. CoRR (2024)
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR (2024)
Zexing Xu, Linjun Zhang, Sitan Yang, Nan Jiang
Peak Period Demand Forecasting with Proxy Data: GNN-Enhanced Meta-Learning. WACV (Workshops) (2024)
Zhe Zhang, Ryumei Nakada, Linjun Zhang
Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference. CoRR (2024)
Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork
Set-Based Prompting: Provably Solving the Language Model Order Dependency Problem. CoRR (2024)
Ryumei Nakada, Yichen Xu, Lexin Li, Linjun Zhang
Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance. CoRR (2024)
Zongbo Han, Yifeng Yang, Changqing Zhang, Linjun Zhang, Joey Tianyi Zhou, Qinghua Hu, Huaxiu Yao
Selective Learning: Towards Robust Calibration with Dynamic Regularization. CoRR (2024)
Zexing Xu, Linjun Zhang, Sitan Yang, Rasoul Etesami, Hanghang Tong, Huan Zhang, Jiawei Han
F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data. CoRR (2024)
Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. CoRR (2024)
Sai Li, Linjun Zhang
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality. CoRR (2024)
Puheng Li, James Zou, Linjun Zhang
FaiREE: fair classification with finite-sample and distribution-free guarantee. ICLR (2023)
Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. CoRR (2023)
Zhun Deng, Cynthia Dwork, Linjun Zhang
HappyMap : A Generalized Multicalibration Method. ITCS (2023)
Haotian Ye, James Zou, Linjun Zhang
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. AISTATS (2023)
Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS (2023)
Xinming Tu, James Zou, Weijie J. Su, Linjun Zhang
What Should Data Science Education Do with Large Language Models? CoRR (2023)
Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes
Reinforcement Learning with Stepwise Fairness Constraints. AISTATS (2023)
Alyssa Huang, Peihan Liu, Ryumei Nakada, Linjun Zhang, Wanrong Zhang
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training. CoRR (2023)
Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR (2023)
Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei
Conformal Prediction for Deep Classifier via Label Ranking. CoRR (2023)
Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR (2023)
Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou
Discover and Cure: Concept-aware Mitigation of Spurious Correlation. ICML (2023)
Mert Yüksekgönül, Linjun Zhang, James Zou, Carlos Guestrin
Beyond Confidence: Reliable Models Should Also Consider Atypicality. CoRR (2023)
Chenhang Cui, Yiyang Zhou, Xinyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao
Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges. CoRR (2023)
T. Tony Cai, Yichen Wang, Linjun Zhang
Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning. CoRR (2023)
Zhun Deng, Cynthia Dwork, Linjun Zhang
HappyMap: A Generalized Multi-calibration Method. CoRR (2023)
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR (2023)
Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin
Beyond Confidence: Reliable Models Should Also Consider Atypicality. NeurIPS (2023)
Haotian Ye, James Zou, Linjun Zhang
Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. CoRR (2022)
Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn
Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR (2022)
Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn
Improving Out-of-Distribution Robustness via Selective Augmentation. ICML (2022)
Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. CoRR (2022)
Huaxiu Yao, Linjun Zhang, Chelsea Finn
Meta-Learning with Fewer Tasks through Task Interpolation. ICLR (2022)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
When and How Mixup Improves Calibration. ICML (2022)
Puheng Li, James Zou, Linjun Zhang
FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee. CoRR (2022)
Kenji Kawaguchi, Linjun Zhang, Zhun Deng
Understanding Dynamics of Nonlinear Representation Learning and Its Application. Neural Comput. 34 (4) (2022)
Zhun Deng, He Sun, Zhiwei Steven Wu, Linjun Zhang, David C. Parkes
Reinforcement Learning with Stepwise Fairness Constraints. CoRR (2022)
Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn
C-Mixup: Improving Generalization in Regression. CoRR (2022)
Junfeng Lin, Linjun Zhang, Runhua Guo, Saiyi Jiao, Xiaomeng Song, Suting Feng, Ke Wang, Mingyang Li, Yudan Luo, Zaizhu Han
The influence of visual deprivation on the development of the thalamocortical network: Evidence from congenitally blind children and adults. NeuroImage 264 (2022)
Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn
C-Mixup: Improving Generalization in Regression. NeurIPS (2022)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
When and How Mixup Improves Calibration. CoRR (2021)
Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou
Adversarial Training Helps Transfer Learning via Better Representations. CoRR (2021)
Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou
Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS (2021)
Zhe Zhang, Linjun Zhang
High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees. CoRR (2021)
Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR (2021)
Kenji Kawaguchi, Linjun Zhang, Zhun Deng
Understanding Dynamics of Nonlinear Representation Learning and Its Application. CoRR (2021)
Sanghoon Oh, Linjun Zhang, H. Eric Tseng, Lu Xu, Gábor Orosz
smooth, curvature constrained, local motion planning for automated vehicles. CCTA (2021)
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS (2021)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou
How Does Mixup Help With Robustness and Generalization? ICLR (2021)
Jinshuo Dong, Weijie J. Su, Linjun Zhang
A Central Limit Theorem for Differentially Private Query Answering. CoRR (2021)
Huaxiu Yao, Linjun Zhang, Chelsea Finn
Meta-Learning with Fewer Tasks through Task Interpolation. CoRR (2021)
Maya Burhanpurkar, Zhun Deng, Cynthia Dwork, Linjun Zhang
Scaffolding Sets. CoRR (2021)
Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
Improving Generalization in Meta-learning via Task Augmentation. ICML (2021)
Jinshuo Dong, Weijie J. Su, Linjun Zhang
A Central Limit Theorem for Differentially Private Query Answering. NeurIPS (2021)
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou
How Does Mixup Help With Robustness and Generalization? CoRR (2020)
Jin Cao, Yibo Zhao, Linjun Zhang, Jason Li
A Lightweight Algorithm to Uncover Deep Relationships in Data Tables. CoRR (2020)
Linjun Zhang, Eric Tseng
Motion Prediction of Human-Driven Vehicles in Mixed Traffic with Connected Autonomous Vehicles. ACC (2020)
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Interpreting Robust Optimization via Adversarial Influence Functions. CoRR (2020)
Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR (2020)
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Interpreting Robust Optimization via Adversarial Influence Functions. ICML (2020)
Qiang Lin, Zhengxing Man, Yongchun Cao, Tao Deng, Chengcheng Han, Chuangui Cao, Linjun Zhang, Sitao Zeng, Ruiting Gao, Weilan Wang, Jinshui Ji, Xiaodi Huang
Classifying functional nuclear images with convolutional neural networks: a survey. IET Image Process. 14 (14) (2020)
T. Tony Cai, Yichen Wang, Linjun Zhang
The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds. CoRR (2020)
T. Tony Cai, Yichen Wang, Linjun Zhang
The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy. CoRR (2019)
Zhonghu Xu, Linjun Zhang, Jinqi Shen, Hao Zhou, Xuefeng Liu, Jiannong Cao, Kai Xing
MRCS: matrix recovery-based communication-efficient compressive sampling on temporal-spatial data of dynamic-scale sparsity in large-scale environmental IoT networks. EURASIP J. Wirel. Commun. Netw. 2019 (2019)
Linjun Zhang, Jing Sun, Gábor Orosz
Hierarchical Design of Connected Cruise Control in the Presence of Information Delays and Uncertain Vehicle Dynamics. IEEE Trans. Control. Syst. Technol. 26 (1) (2018)
Linjun Zhang, Gábor Orosz
Beyond-Line-of-Sight Identification by Using Vehicle-to-Vehicle Communication. IEEE Trans. Intell. Transp. Syst. 19 (6) (2018)
Linjun Zhang, Gábor Orosz
Black-box modeling of connected vehicle networks. ACC (2016)
Linjun Zhang, Gábor Orosz
Motif-Based Design for Connected Vehicle Systems in Presence of Heterogeneous Connectivity Structures and Time Delays. IEEE Trans. Intell. Transp. Syst. 17 (6) (2016)
Linjun Zhang, Gábor Orosz
Nonlinear dynamics of connected vehicle systems with communication delays. ACC (2015)
Michael Small, Kevin Judd, Linjun Zhang
How is that complex network complex? ISCAS (2014)
Linjun Zhang, Michael Small, Kevin Judd
Exactly scale-free scale-free networks. CoRR (2013)
Linjun Zhang, Jinkun Liu
Nonlinear PDE observer design for a flexible two-link manipulator. ACC (2012)
Linjun Zhang, Jinkun Liu
Optimal trajectory control of flexible two-link manipulator based on PDE model. CDC (2012)
Jingjing Zhao, Hua Shu, Linjun Zhang, Xiaoyi Wang, Qiyong Gong, Ping Li
Cortical competition during language discrimination. NeuroImage 43 (3) (2008)