Linjun Zhang - RankMe

126 papers A* 24A 5C 5Journal 86Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Statistical Framework for Alignment with Biased AI Feedback. CoRR Xintao Xia, Zhiqiu Xia, Linjun Zhang, Zhanrui Cai
2026	J	`jnl`	Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training. CoRR Ran Xu, Tianci Liu, Zihan Dong, Tony Yu, Ilgee Hong, Carl Yang, Linjun Zhang, Tao Zhao, Haoyu Wang
2026	J	`jnl`	Equitable Evaluation via Elicitation. CoRR Elbert Du, Cynthia Dwork, Lunjia Hu, Reid McIlroy-Young, Han Shao, Linjun Zhang
2026	J	`jnl`	Evaluating LLMs When They Do Not Know the Answer: Statistical Evaluation of Mathematical Reasoning via Comparative Signals. CoRR Zihan Dong, Zhixian Zhang, Yang Zhou, Can Jin, Ruijia Wu, Linjun Zhang
2026	J	`jnl`	Labels or Preferences? Budget-Constrained Learning with Human Judgments over AI-Generated Outputs. CoRR Zihan Dong, Ruijia Wu, Linjun Zhang
2026	—	`conf`	PEANuT: Parameter-Efficient Adaptation with Weight-aware Neural Tweakers. KDD (1) Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang
2026	J	`jnl`	PieArena: Frontier Language Agents Achieve MBA-Level Negotiation Performance and Reveal Novel Behavioral Differences. CoRR Chris Zhu, Sasha Cui, Will Sanok Dufallo, Runzhi Jin, Zhen Xu, Linjun Zhang, Daylian Cain
2026	J	`jnl`	Reliable and Responsible Foundation Models: A Comprehensive Survey. CoRR Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2026	J	`jnl`	Unified Inference Framework for Single and Multi-Player Performative Prediction: Method and Asymptotic Optimality. CoRR Zhixian Zhang, Xiaotian Hou, Linjun Zhang
2025	J	`jnl`	A Statistical Hypothesis Testing Framework for Data Misappropriation Detection in Large Language Models. CoRR Yinpeng Cai, Lexin Li, Linjun Zhang
2025	J	`jnl`	A Theoretical Framework for Prompt Engineering: Approximating Smooth Functions with Transformer Prompts. CoRR Ryumei Nakada, Wenlong Ji, Tianxi Cai, James Zou, Linjun Zhang
2025	J	`jnl`	AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play. CoRR Ran Xu, Yuchen Zhuang, Zihan Dong, Jonathan Wang, Yue Yu, Joyce C. Ho, Linjun Zhang, Haoyu Wang, Wenqi Shi, Carl Yang
2025	J	`jnl`	Alignment Tipping Process: How Self-Evolution Pushes LLM Agents Off the Rails. CoRR Siwei Han, Jiaqi Liu, Yaofeng Su, Wenbo Duan, Xinyuan Liu, Cihang Xie, Mohit Bansal, Mingyu Ding, Linjun Zhang, Huaxiu Yao
2025	J	`jnl`	An Overview of Large Language Models for Statisticians. CoRR Wenlong Ji, Weizhe Yuan, Emily J. Getzen, Kyunghyun Cho, Michael I. Jordan, Song Mei, Jason Aaron Edward Weston, Weijie J. Su, Jing Xu, Linjun Zhang
2025	J	`jnl`	Bias-Corrected Data Synthesis for Imbalanced Learning. CoRR Pengfei Lyu, Zhengchi Ma, Linjun Zhang, Anru R. Zhang
2025	J	`jnl`	Contrastive Network Representation Learning. CoRR Zihan Dong, Xin Zhou, Ryumei Nakada, Lexin Li, Linjun Zhang
2025	—	`conf`	Differentially Private Learning Beyond the Classical Dimensionality Regime. TCC (4) Cynthia Dwork, Pranay Tankala, Linjun Zhang
2025	A*	`conf`	FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees. ICML Fan Nie, Xiaotian Hou, Shuhang Lin, James Zou, Huaxiu Yao, Linjun Zhang
2025	A*	`conf`	MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models. ICLR Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao
2025	A*	`conf`	MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment. ICML Tianze Wang, Dongnan Gui, Yifan Hu, Shuhang Lin, Linjun Zhang
2025	J	`jnl`	MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment. CoRR Tianze Wang, Dongnan Gui, Yifan Hu, Shuhang Lin, Linjun Zhang
2025	J	`jnl`	Microseismic Source Location Based on Full Waveform Inversion-Driven Neural Network. Int. J. Comput. Intell. Syst. Yan Zhang, Zixin Wei, Yongxue Zhang, Hongli Dong, Jingzhe Wang, Linjun Zhang, Liwei Song
2025	A*	`conf`	Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing. ICML Tianci Liu, Ruirui Li, Zihan Dong, Hui Liu, Xianfeng Tang, Qingyu Yin, Linjun Zhang, Haoyu Wang, Jing Gao
2025	J	`jnl`	Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing. CoRR Tianci Liu, Zihan Dong, Linjun Zhang, Haoyu Wang, Jing Gao
2025	J	`jnl`	Optimas: Optimizing Compound AI Systems with Globally Aligned Local Rewards. CoRR Shirley Wu, Parth Sarthi, Shiyu Zhao, Aaron Lee, Herumb Shandilya, Adrian Mladenic Grobelnik, Nurendra Choudhary, Edward W. Huang, Karthik Subbian, Linjun Zhang, Diyi Yang, James Zou, Jure Leskovec
2025	J	`jnl`	Reliable and Responsible Foundation Models. Trans. Mach. Learn. Res. Xinyu Yang, Junlin Han, Rishi Bommasani, Jinqi Luo, Wenjie Qu, Wangchunshu Zhou, Adel Bibi, Xiyao Wang, Jaehong Yoon, Elias Stengel-Eskin, Shengbang Tong, Lingfeng Shen, Rafael Rafailov, Runjia Li, Zhaoyang Wang, Yiyang Zhou, Chenhang Cui, Yu Wang, Wenhao Zheng, Huichi Zhou, Jindong Gu, Zhaorun Chen, Peng Xia, Tony Lee, Thomas P. Zollo, Vikash Sehwag, Jixuan Leng, Jiuhai Chen, Yuxin Wen, Huan Zhang, Zhun Deng, Linjun Zhang, Pavel Izmailov, Pang Wei Koh, Yulia Tsvetkov, Andrew Gordon Wilson, Jiaheng Zhang, James Zou, Cihang Xie, Hao Wang, Philip Torr, Julian J. McAuley, David Alvarez-Melis, Florian Tramèr, Kaidi Xu, Suman Jana, Chris Callison-Burch, René Vidal, Filippos Kokkinos, Mohit Bansal, Beidi Chen, Huaxiu Yao
2025	J	`jnl`	Residual Feature Integration is Sufficient to Prevent Negative Transfer. CoRR Yichen Xu, Ryumei Nakada, Linjun Zhang, Lexin Li
2025	—	`conf`	RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization. ACL (Findings) Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang
2025	J	`jnl`	RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization. CoRR Tianci Liu, Haoxiang Jiang, Tianze Wang, Ran Xu, Yue Yu, Linjun Zhang, Tuo Zhao, Haoyu Wang
2025	J	`jnl`	Secret-Protected Evolution for Differentially Private Synthetic Text Generation. CoRR Tianze Wang, Zhaoyu Chen, Jian Du, Yingtai Xiao, Linjun Zhang, Qiang Yan
2025	J	`jnl`	Statistical Inference for Differentially Private Stochastic Gradient Descent. CoRR Xintao Xia, Linjun Zhang, Zhanrui Cai
2025	J	`jnl`	To Err Is Human: Systematic Quantification of Errors in Published AI Papers via LLM Analysis. CoRR Federico Bianchi, Yongchan Kwon, Zachary Izzo, Linjun Zhang, James Zou
2025	J	`jnl`	UQ: Assessing Language Models on Unsolved Questions. CoRR Fan Nie, Ken Ziyu Liu, Zihao Wang, Rui Sun, Wei Liu, Weijia Shi, Huaxiu Yao, Linjun Zhang, Andrew Y. Ng, James Zou, Sanmi Koyejo, Yejin Choi, Percy Liang, Niklas Muennighoff
2024	A*	`conf`	Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
2024	A*	`conf`	Calibrated Self-Rewarding Vision Language Models. NeurIPS Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao
2024	J	`jnl`	Calibrated Self-Rewarding Vision Language Models. CoRR Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao
2024	J	`jnl`	Can AI Be as Creative as Humans? CoRR Haonan Wang, James Zou, Michael Mozer, Anirudh Goyal, Alex Lamb, Linjun Zhang, Weijie J. Su, Zhun Deng, Michael Qizhe Xie, Hannah Brown, Kenji Kawaguchi
2024	A*	`conf`	Conformal Prediction for Deep Classifier via Label Ranking. ICML Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei
2024	J	`jnl`	Contrastive Learning on Multimodal Analysis of Electronic Health Records. CoRR Tianxi Cai, Feiqing Huang, Ryumei Nakada, Linjun Zhang, Doudou Zhou
2024	J	`jnl`	Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference. CoRR Zhe Zhang, Ryumei Nakada, Linjun Zhang
2024	J	`jnl`	Differentially Private Learning Beyond the Classical Dimensionality Regime. CoRR Cynthia Dwork, Pranay Tankala, Linjun Zhang
2024	J	`jnl`	Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm. CoRR Xintao Xia, Linjun Zhang, Zhanrui Cai
2024	J	`jnl`	Distribution-Free Fair Federated Learning with Small Samples. CoRR Qichuan Yin, Junzhou Huang, Huaxiu Yao, Linjun Zhang
2024	J	`jnl`	F-FOMAML: GNN-Enhanced Meta-Learning for Peak Period Demand Forecasting with Proxy Data. CoRR Zexing Xu, Linjun Zhang, Sitan Yang, S. Rasoul Etesami, Hanghang Tong, Huan Zhang, Jiawei Han
2024	J	`jnl`	FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality. CoRR Sai Li, Linjun Zhang
2024	J	`jnl`	FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees. CoRR Fan Nie, Xiaotian Hou, Shuhang Lin, James Zou, Huaxiu Yao, Linjun Zhang
2024	A*	`conf`	Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks. ICML Lujing Zhang, Aaron Roth, Linjun Zhang
2024	J	`jnl`	Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks. CoRR Lujing Zhang, Aaron Roth, Linjun Zhang
2024	J	`jnl`	Foreword for the Collection of Papers from the Workshop on the Analysis of Census Noisy Measurement Files and Differential Privacy. J. Priv. Confidentiality Jörg Drechsler, Ruobin Gong, Weijie Su, Linjun Zhang
2024	J	`jnl`	MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models. CoRR Peng Xia, Kangyu Zhu, Haoran Li, Tianze Wang, Weijia Shi, Sheng Wang, Linjun Zhang, James Zou, Huaxiu Yao
2024	J	`jnl`	NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models. CoRR Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang
2024	A*	`conf`	Order-Independence Without Fine Tuning. NeurIPS Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork
2024	—	`conf`	Peak Period Demand Forecasting with Proxy Data: GNN-Enhanced Meta-Learning. WACV (Workshops) Zexing Xu, Linjun Zhang, Sitan Yang, Nan Jiang
2024	J	`jnl`	Provable Multi-Party Reinforcement Learning with Diverse Human Feedback. CoRR Huiying Zhong, Zhun Deng, Weijie J. Su, Zhiwei Steven Wu, Linjun Zhang
2024	A*	`conf`	RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. EMNLP Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao
2024	J	`jnl`	RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. CoRR Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao
2024	A*	`conf`	S NeurIPS Xinyu Yang, Jixuan Leng, Geyang Guo, Jiawei Zhao, Ryumei Nakada, Linjun Zhang, Huaxiu Yao, Beidi Chen
2024	J	`jnl`	S CoRR Xinyu Yang, Jixuan Leng, Geyang Guo, Jiawei Zhao, Ryumei Nakada, Linjun Zhang, Huaxiu Yao, Beidi Chen
2024	J	`jnl`	Selective Learning: Towards Robust Calibration with Dynamic Regularization. CoRR Zongbo Han, Yifeng Yang, Changqing Zhang, Linjun Zhang, Joey Tianyi Zhou, Qinghua Hu, Huaxiu Yao
2024	J	`jnl`	Set-Based Prompting: Provably Solving the Language Model Order Dependency Problem. CoRR Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork
2024	J	`jnl`	Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance. CoRR Ryumei Nakada, Yichen Xu, Lexin Li, Linjun Zhang
2023	J	`jnl`	Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
2023	A*	`conf`	Beyond Confidence: Reliable Models Should Also Consider Atypicality. NeurIPS Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin
2023	J	`jnl`	Beyond Confidence: Reliable Models Should Also Consider Atypicality. CoRR Mert Yüksekgönül, Linjun Zhang, James Zou, Carlos Guestrin
2023	J	`jnl`	Conformal Prediction for Deep Classifier via Label Ranking. CoRR Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei
2023	A*	`conf`	Discover and Cure: Concept-aware Mitigation of Spurious Correlation. ICML Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou
2023	J	`jnl`	Discover and Cure: Concept-aware Mitigation of Spurious Correlation. CoRR Shirley Wu, Mert Yüksekgönül, Linjun Zhang, James Zou
2023	A*	`conf`	FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. ICLR Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
2023	A*	`conf`	FaiREE: fair classification with finite-sample and distribution-free guarantee. ICLR Puheng Li, James Zou, Linjun Zhang
2023	A	`conf`	Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. AISTATS Haotian Ye, James Zou, Linjun Zhang
2023	A	`conf`	HappyMap : A Generalized Multicalibration Method. ITCS Zhun Deng, Cynthia Dwork, Linjun Zhang
2023	J	`jnl`	HappyMap: A Generalized Multi-calibration Method. CoRR Zhun Deng, Cynthia Dwork, Linjun Zhang
2023	J	`jnl`	Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges. CoRR Chenhang Cui, Yiyang Zhou, Xinyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao
2023	A	`conf`	Reinforcement Learning with Stepwise Fairness Constraints. AISTATS Zhun Deng, He Sun, Steven Wu, Linjun Zhang, David C. Parkes
2023	J	`jnl`	Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training. CoRR Alyssa Huang, Peihan Liu, Ryumei Nakada, Linjun Zhang, Wanrong Zhang
2023	J	`jnl`	Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning. CoRR T. Tony Cai, Yichen Wang, Linjun Zhang
2023	J	`jnl`	The Power of Contrast for Feature Learning: A Theoretical Analysis. J. Mach. Learn. Res. Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
2023	A	`conf`	Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
2023	J	`jnl`	Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
2023	J	`jnl`	What Should Data Science Education Do with Large Language Models? CoRR Xinming Tu, James Zou, Weijie J. Su, Linjun Zhang
2022	A*	`conf`	C-Mixup: Improving Generalization in Regression. NeurIPS Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn
2022	J	`jnl`	C-Mixup: Improving Generalization in Regression. CoRR Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn
2022	J	`jnl`	FIFA: Making Fairness More Generalizable in Classifiers Trained on Imbalanced Data. CoRR Zhun Deng, Jiayao Zhang, Linjun Zhang, Ting Ye, Yates Coley, Weijie J. Su, James Zou
2022	J	`jnl`	FaiREE: Fair Classification with Finite-Sample and Distribution-Free Guarantee. CoRR Puheng Li, James Zou, Linjun Zhang
2022	J	`jnl`	Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise. CoRR Haotian Ye, James Zou, Linjun Zhang
2022	A*	`conf`	Improving Out-of-Distribution Robustness via Selective Augmentation. ICML Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn
2022	J	`jnl`	Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn
2022	A*	`conf`	Meta-Learning with Fewer Tasks through Task Interpolation. ICLR Huaxiu Yao, Linjun Zhang, Chelsea Finn
2022	J	`jnl`	Reinforcement Learning with Stepwise Fairness Constraints. CoRR Zhun Deng, He Sun, Zhiwei Steven Wu, Linjun Zhang, David C. Parkes
2022	J	`jnl`	The influence of visual deprivation on the development of the thalamocortical network: Evidence from congenitally blind children and adults. NeuroImage Junfeng Lin, Linjun Zhang, Runhua Guo, Saiyi Jiao, Xiaomeng Song, Suting Feng, Ke Wang, Mingyang Li, Yudan Luo, Zaizhu Han
2022	J	`jnl`	Understanding Dynamics of Nonlinear Representation Learning and Its Application. Neural Comput. Kenji Kawaguchi, Linjun Zhang, Zhun Deng
2022	A*	`conf`	When and How Mixup Improves Calibration. ICML Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
2021	A*	`conf`	A Central Limit Theorem for Differentially Private Query Answering. NeurIPS Jinshuo Dong, Weijie J. Su, Linjun Zhang
2021	J	`jnl`	A Central Limit Theorem for Differentially Private Query Answering. CoRR Jinshuo Dong, Weijie J. Su, Linjun Zhang
2021	A*	`conf`	Adversarial Training Helps Transfer Learning via Better Representations. NeurIPS Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Y. Zou
2021	J	`jnl`	Adversarial Training Helps Transfer Learning via Better Representations. CoRR Zhun Deng, Linjun Zhang, Kailas Vodrahalli, Kenji Kawaguchi, James Zou
2021	—	`conf`	G CCTA Sanghoon Oh, Linjun Zhang, H. Eric Tseng, Lu Xu, Gábor Orosz
2021	J	`jnl`	High-Dimensional Differentially-Private EM Algorithm: Methods and Near-Optimal Statistical Guarantees. CoRR Zhe Zhang, Linjun Zhang
2021	A*	`conf`	How Does Mixup Help With Robustness and Generalization? ICLR Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Zou
2021	A	`conf`	Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. AISTATS Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Zou
2021	A*	`conf`	Improving Generalization in Meta-learning via Task Augmentation. ICML Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
2021	J	`jnl`	Meta-Learning with Fewer Tasks through Task Interpolation. CoRR Huaxiu Yao, Linjun Zhang, Chelsea Finn
2021	J	`jnl`	Scaffolding Sets. CoRR Maya Burhanpurkar, Zhun Deng, Cynthia Dwork, Linjun Zhang
2021	J	`jnl`	The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
2021	J	`jnl`	Understanding Dynamics of Nonlinear Representation Learning and Its Application. CoRR Kenji Kawaguchi, Linjun Zhang, Zhun Deng
2021	J	`jnl`	When and How Mixup Improves Calibration. CoRR Linjun Zhang, Zhun Deng, Kenji Kawaguchi, James Zou
2020	J	`jnl`	A Lightweight Algorithm to Uncover Deep Relationships in Data Tables. CoRR Jin Cao, Yibo Zhao, Linjun Zhang, Jason Li
2020	J	`jnl`	Classifying functional nuclear images with convolutional neural networks: a survey. IET Image Process. Qiang Lin, Zhengxing Man, Yongchun Cao, Tao Deng, Chengcheng Han, Chuangui Cao, Linjun Zhang, Sitao Zeng, Ruiting Gao, Weilan Wang, Jinshui Ji, Xiaodi Huang
2020	J	`jnl`	How Does Mixup Help With Robustness and Generalization? CoRR Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, James Y. Zou
2020	J	`jnl`	Improving Adversarial Robustness via Unlabeled Out-of-Domain Data. CoRR Zhun Deng, Linjun Zhang, Amirata Ghorbani, James Y. Zou
2020	A*	`conf`	Interpreting Robust Optimization via Adversarial Influence Functions. ICML Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
2020	J	`jnl`	Interpreting Robust Optimization via Adversarial Influence Functions. CoRR Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
2020	C	`conf`	Motion Prediction of Human-Driven Vehicles in Mixed Traffic with Connected Autonomous Vehicles. ACC Linjun Zhang, Eric H. Tseng
2020	J	`jnl`	The Cost of Privacy in Generalized Linear Models: Algorithms and Minimax Lower Bounds. CoRR T. Tony Cai, Yichen Wang, Linjun Zhang
2019	J	`jnl`	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. Zhonghu Xu, Linjun Zhang, Jinqi Shen, Hao Zhou, Xuefeng Liu, Jiannong Cao, Kai Xing
2019	J	`jnl`	The Cost of Privacy: Optimal Rates of Convergence for Parameter Estimation with Differential Privacy. CoRR T. Tony Cai, Yichen Wang, Linjun Zhang
2018	J	`jnl`	Beyond-Line-of-Sight Identification by Using Vehicle-to-Vehicle Communication. IEEE Trans. Intell. Transp. Syst. Linjun Zhang, Gábor Orosz
2018	J	`jnl`	Hierarchical Design of Connected Cruise Control in the Presence of Information Delays and Uncertain Vehicle Dynamics. IEEE Trans. Control. Syst. Technol. Linjun Zhang, Jing Sun, Gábor Orosz
2016	C	`conf`	Black-box modeling of connected vehicle networks. ACC Linjun Zhang, Gábor Orosz
2016	J	`jnl`	Motif-Based Design for Connected Vehicle Systems in Presence of Heterogeneous Connectivity Structures and Time Delays. IEEE Trans. Intell. Transp. Syst. Linjun Zhang, Gábor Orosz
2015	C	`conf`	Nonlinear dynamics of connected vehicle systems with communication delays. ACC Linjun Zhang, Gábor Orosz
2014	C	`conf`	How is that complex network complex? ISCAS Michael Small, Kevin Judd, Linjun Zhang
2013	J	`jnl`	Exactly scale-free scale-free networks. CoRR Linjun Zhang, Michael Small, Kevin Judd
2012	C	`conf`	Nonlinear PDE observer design for a flexible two-link manipulator. ACC Linjun Zhang, Jinkun Liu
2012	—	`conf`	Optimal trajectory control of flexible two-link manipulator based on PDE model. CDC Linjun Zhang, Jinkun Liu
2008	J	`jnl`	Cortical competition during language discrimination. NeuroImage Jingjing Zhao, Hua Shu, Linjun Zhang, Xiaoyi Wang, Qiyong Gong, Ping Li