Provable Responsible AI and Data Analytics Lab

Multi-hop Question Answering under Temporal Knowledge Editing

Keyuan Cheng, Gang Lin, Haoyang Fei, Yuxuan Zhai, Lu Yu, Muhammad Asif Ali, Lijie Hu, Di Wang

Conference on Language Modeling (COLM 2024)

MONAL: Model Autophagy Analysis for Modeling Human-AI Interactions

Shu Yang, Muhammad Asif Ali, Lu Yu, Lijie Hu, Di Wang

Conference on Language Modeling (COLM 2024)

SATO: Stable Text-to-Motion Framework

Wenshuo Chen, Hongru Xiao, Erhang Zhang, Lijie Hu, Lei Wang, Mengyuan Liu, and Chen Chen

ACM Multimedia Conference (ACM MM 2024)

Autonomous Workflow for Multimodal Fine-Grained Training Assistants Towards Mixed Reality

Jiahuan Pei, Irene Viola, Haochen Huang, Junxiao Wang, Moonisa Ahsan, Fanghua Ye, Jiang Yiming, Yao Sai, Di Wang, Zhumin Chen, Pengjie Ren, Pablo Cesar

Annual Meeting of the Association for Computational Linguistics (ACL 2024 Findings)

Improving Interpretation Faithfulness for Vision Transformers

Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

International Conference on Machine Learning (ICML 2024)

Understanding Forgetting in Continual Learning with Linear Regression

Meng Ding, Kaiyi Ji, Di Wang, Jinhui Xu

International Conference on Machine Learning (ICML 2024)

Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization

Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal

International Conference on Machine Learning (ICML 2024)

Preserving Node-level Privacy in Graph Neural Networks

Zihang Xiang, Tianhao Wang, Di Wang

IEEE Symposium on Security and Privacy (IEEE S&P 2024)

Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET)

Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang

Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024 Findings)

Differentially Private Natural Language Models: Recent Advances and Future Direction

Lijie Hu, Ivan Habernal, Lei Shen, and Di Wang

Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024 Findings)

Faithful Vision-Language Interpretation via Concept Bottleneck Models

Songning Lai, Lijie Hu, Junxiao Wang, Laure Berti-Equille, Di Wang

International Conference on Learning Representations (ICLR 2024)

Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model

Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang

International Conference on Learning Representations (ICLR 2024)

Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach

Shaopeng Fu, Di Wang

International Conference on Learning Representations (ICLR 2024)

An LLM can Fool Itself: A Prompt-Based Adversarial Attack

Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan Kankanhalli

International Conference on Learning Representations (ICLR 2024)

Privacy Amplification via Shuffling: Unified, Simplified, and Tightened

Shaowei Wang, Yun Peng, Jin Li, Zikai Wen, Zhipeng Li, Shiyu Yu, Di Wang, Wei Yang

International Conference on Very Large Data Bases (VLDB 2024)

Communication Efficient and Provable Federated Unlearning

Youming Tao, Cheng-Long Wang, Miao Pan, Dongxiao Yu, Xiuzhen Cheng, and Di Wang

International Conference on Very Large Data Bases (VLDB 2024)

GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings

Muhammad Asif Ali, Maha Alshmrani, Jianbin Qin, Yan Hu, Di Wang

Arabic Natural Language Processing Conference (ArabicNLP 2023)

GRI: Graph-based Relative Isomorphism of Word Embedding Spaces

Muhammad Asif Ali, Yan Hu, Jianbin Qin, Di Wang

Conference on Empirical Methods in Natural Language Processing (EMNLP 2023 Findings)

DetectLLM: Leveraging Log Rank Information for Zero-Shot Detection of Machine-Generated Text

Jinyan Su, Terry Yue Zhuo, Di Wang, Preslav Nakov

Conference on Empirical Methods in Natural Language Processing (EMNLP 2023 Findings)

On Private and Robust Bandits

Yulian Wu, Xingyu Zhou, Youming Tao, Di Wang

Conference on Neural Information Processing Systems (NeurIPS 2023)

Towards Test-time Refusals via Concept Negation

Peiran Dong, Song Guo, Junxiao Wang, Bingjie Wang, Jiewei Zhang, Ziming Liu

Conference on Neural Information Processing Systems (NeurIPS 2023)

Finite Sample Guarantees of Differentially Private Expectation Maximization Algorithm

Di Wang, Jiahao Ding, Lijie Hu, Zejun Xie, Miao Pan, Jinhui Xu

European Conference on Artificial Intelligence (ECAI 2023)

Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited

Jinyan Su, Changhong Zhao, Di Wang

Conference on Uncertainty in Artificial Intelligence (UAI 2023)

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards

Yulian Wu, Xingyu Zhou, Sayak Ray Chowdhury, Di Wang

International Conference on Machine Learning (ICML 2023)

Investigating Trojan Attacks on Pre-trained Language Model-powered Database Middleware

Peiran Dong, Song Guo, Junxiao Wang

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)

Pfedprompt: Learning personalized prompt for vision-language models in federated learning

Tao Guo, Song Guo, Junxiao Wang

ACM Web Conference (WWW 2023)

Pmr: Prototypical modal rebalance for multimodal learning

Yunfeng Fan, Wenchao Xu, Haozhao Wang, Junxiao Wang, Song Guo

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023)

Inductive Graph Unlearning

Cheng-Long Wang, Mengdi Huai, and Di Wang

USENIX Security Symposium (USENIX 2023)

A Theory to Instruct Differentially-Private Learning via Clipping Bias Reduction

Hanshen Xiao, Zihang Xiang, Di Wang, and Srini Devadas

IEEE Symposium on Security and Privacy (IEEE S&P 2023)

High-Speed Wireless Communications Inspired Energy Efficient Federated Learning over Mobile Devices

Rui Chen, Qiyu Wan, Xinyue Zhang, Xiaoqi Qin, Di Wang, Xin Fu, Miao Pan

ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2023)

Practical Differentially Private and Byzantine-resilient Federated Learning

Zihang Xiang, Tianhao Wang , Wanyu Lin, and Di Wang

International Conference on Management of Data (SIGMOD 2023)

Privacy-preserving Sparse Generalized Eigenvalue Problem

Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang

International Conference on Artificial Intelligence and Statistics (AISTATS 2023)

SEAT: Stable and Explainable Attention

Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang

AAAI Conference on Artificial Intelligence (AAAI 2023)

TabMentor: Detect Errors on Tabular Data with Noisy Labels

Yaru Zhang, Jianbin Qin, Yaoshu Wang, Muhammad Asif Ali, Yan Ji, Rui Mao

International Conference on Advanced Data Mining and Applications (ADMA 2023)

Adaptive Label Cleaning for Error Detection on Tabular Data

Yaru Zhang, Jianbin Qin, Rui Mao, Yan Ji, Yaoshu Wang, Muhammad Asif Ali

Asia-Pacific Web and Web-Age Information Management Joint International Conference on Web and Big Data (APWeb-WAIM 2023)

Learning and Deducing Temporal Orders

Wenfei Fan, Resul Tugay, Yaoshu Wang, Min Xie, Muhammad Asif Ali

International Conference on Very Large Data Bases (VLDB 2023)

Truthful Generalized Linear Models

Yuan Qiu, Jinyan Liu, Di Wang

Conference on Web and Internet Economics (WINE 2022)

On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data

Jinyan Su, Jinhui Xu, Di Wang

Asian Conference on Machine Learning (ACML 2022)

Differentially Private l1-norm Linear Regression with Heavy-tailed Data

Di Wang, Jinhui Xu

IEEE International Symposium on Information Theory (ISIT 2022)

Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited

Youming Tao, Yulian Wu, Xiuzhen Cheng, and Di Wang

International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2022)

Faster Rates of Private Stochastic Convex Optimization

Jinyan Su, Lijie Hu, Di Wang

International Conference on Algorithmic Learning Theory (ALT 2022)

Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits

Youming Tao, Yulian Wu, Peng Zhao, and Di Wang

International Conference on Artificial Intelligence and Statistics (AISTATS 2022)

On Facility Location Problem in the Local Differential Privacy Model

Vincent Cohen-Addad, Yunus Esencayi, Chenglin Fan, Marco Gaboradi, Shi Li, Di Wang

International Conference on Artificial Intelligence and Statistics (AISTATS 2022)

High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data

Lijie Hu, Shuo Ni, Hanshen Xiao, and Di Wang

ACM Symposium on Principles of Database Systems (PODS 2022)

Truthful and privacy-preserving generalized linear models

Yuan Qiu, Jinyan Liu, and Di Wang

Information and Computation

Multitask Asynchronous Metalearning for Few-Shot Anomalous Node Detection in Dynamic Networks

Yifan Hong, Chuanqi Shi, Junyang Chen, Huan Wang, Di Wang

IEEE Transactions on Computational Social Systems

Fair Single Index Model

Yidong Wang, Meng Ding, Jinhui Xu, Di Wang

ACM Transactions on Knowledge Discovery from Data

Explore and Cure: Unveiling Sample Effectiveness with Context-Aware Federated Prompt Tuning

Tao Guo, Song Guo, Junxiao Wang

IEEE Transactions on Mobile Computing

Rethinking Personalized Client Collaboration in Federated Learning

Leijie Wu, Song Guo, Yaohong Ding, Junxiao Wang, Wenchao Xu, Yufeng Zhan, Anne-Marie Kermarrec

IEEE Transactions on Mobile Computing

Exploring Amplified Heterogeneity Arising From Heavy-Tailed Distributions in Federated Learning

Yizhi Zhou, Junxiao Wang, Xiangyu Kong, Shan Wu, Xin Xie, Heng Qi

IEEE Transactions on Mobile Computing

Private Over-the-Air Federated Learning at Band-Limited Edge

Youming Tao, Shuzhen Chen, Congwei Zhang, Di Wang, Dongxiao Yu, Xiuzhen Cheng, Falko Dressler

IEEE Transactions on Mobile Computing

Faster Rates of Differentially Private Stochastic Convex Optimization

Jinyan Su, Lijie Hu, and Di Wang

Journal of Machine Learning Research

Persistent Local Homology in Graph Learning

Minghua Wang, Yan Hu, Ziyun Huang, Di Wang, Jinhui Xu

Transactions on Machine Learning Research

A Multi-classification Division-aggregation Framework for Fake News Detection

Wen Zhang, Haitao Fu, Huan Wang, Zhiguo Gong, Pan Zhou, Di Wang

IEEE Transactions on Big Data

Near-perfect Coverage Manifold Estimation in Cellular Networks via conditional GAN

Washim Uddin Mondal, Veni Goyal, Goutam Das, Satish V. Ukkusuri, Di Wang, Mohamed-Slim Alouini, Vaneet Aggarwal

IEEE Networking Letters

Personalized and Privacy-preserving Federated Heterogeneous Medical Image Analysis with PPPML-HMI

Juexiao Zhou, Longxi Zhou, Di Wang, Xiaopeng Xu, Haoyang Li, Yuetan Chu, Wenkai Han, and Xin Gao

Computers in Biology and Medicine

PPML-Omics: a Privacy-Preserving federated Machine Learning System Protects Patients' Privacy from Omic Data

Juexiao Zhou, Siyuan Chen, Yulian Wu, Haoyang Li, Bin Zhang, Longxi Zhou, Yan Hu, Zihang Xiang, Zhongxiao Li, Ningning Chen, Wenkai Han, Di Wang, and Xin Gao

Science Advances

PAC Learning Halfspaces in Non-interactive Local Differential Privacy Model with Public Unlabeled Data

Jinyan Su, Jinhui Xu, and Di Wang

Journal of Computer and System Sciences

Quantizing Heavy-tailed Data in Statistical Estimation:(Near) Minimax Rates, Covariate Quantization, and Uniform Recovery

Junren Chen, Michael Kwok Po NG, Di Wang

IEEE Transactions on Information Theory

Nearly Optimal Rates of Privacy-preserving Sparse Generalized Eigenvalue Problem

Lijie Hu, Zihang Xiang, Jiabin Liu, Di Wang

IEEE Transactions on Knowledge and Data Engineering

High Dimensional Statistical Estimation under Uniformly Dithered One-bit Quantization

Junren Chen, Cheng-Long Wang, Michael Kwok Po NG, Di Wang

IEEE Transactions on Information Theory

Gradient Complexity and Non-stationary Views of Differentially Private Empirical Risk Minimization

Di Wang, Jinhui Xu

Theoretical Computer Science

Generalized Linear Models in Non-interactive Local Differential Privacy with Public Data

Di Wang, Lijie Hu, Huanyu Zhang, Marco Gaboardi, Jinhui Xu

Journal of Machine Learning Research