Quadratic Upper Bound for Recursive Teaching Dimension of Finite VC Classes. - Lunjia Hu; Ruihan Wu; Tianhong Li; Liwei Wang 001 (COLT, 2017)

Product Kernel Interpolation for Scalable Gaussian Processes. - Jacob R. Gardner; Geoff Pleiss; Ruihan Wu; Kilian Q. Weinberger; Andrew Gordon Wilson (AISTATS, 2018)

DumbNet: a smart data center network fabric with dumb switches. - Yiran Li; Da Wei; Xiaoqi Chen; Ziheng Song; Ruihan Wu; Yuxing Li; Xin Jin 008; Wei Xu 005 (EuroSys, 2018)

Scalable Influence Maximization with General Marketing Strategies. - Ruihan Wu; Zheng Yu; Wei Chen 013 (CoRR, 2018)

TrojanNet: Embedding Hidden Trojan Horse Models in Neural Networks. - Chuan Guo 001; Ruihan Wu; Kilian Q. Weinberger (CoRR, 2020)

Correlator Convolutional Neural Networks: An Interpretable Architecture for Image-like Quantum Matter Data. - Cole Miles; Annabelle Bohrdt; Ruihan Wu; Christie Chiu; Muqing Xu; Geoffrey Ji; Markus Greiner; Kilian Q. Weinberger; Eugene Demler; Eun-Ah Kim (CoRR, 2020)

Scalable Lattice Influence Maximization. - Wei Chen 013; Ruihan Wu; Zheng Yu (IEEE Trans. Comput. Soc. Syst., 2020)

Spatial-Temporal Graph Neural Network For Interaction-Aware Vehicle Trajectory Prediction. - Junan Chen; Yan Wang 051; Ruihan Wu; Mark Campbell 001 (CASE, 2021)

Making Paper Reviewing Robust to Bid Manipulation Attacks. - Ruihan Wu; Chuan Guo 001; Felix Wu; Rahul Kidambi; Laurens van der Maaten; Kilian Q. Weinberger (ICML, 2021)

Fixes That Fail: Self-Defeating Improvements in Machine-Learning Systems. - Ruihan Wu; Chuan Guo 001; Awni Y. Hannun; Laurens van der Maaten (NeurIPS, 2021)

Online Adaptation to Label Distribution Shift. - Ruihan Wu; Chuan Guo 001; Yi Su; Kilian Q. Weinberger (NeurIPS, 2021)

Differentially private multi-party data release for linear regression. - Ruihan Wu; Xin Yang 017; Yuanshun Yao; Jiankai Sun; Tianyi Liu; Kilian Q. Weinberger; Chong Wang 002 (UAI, 2022)

Exploring the interaction mechanism between antagonist and the jasmonate receptor complex by molecular dynamics simulation. - Mengqi Cui; Kun Zhang; Ruihan Wu; Juan Du 003 (J. Comput. Aided Mol. Des., 2022)

Does Label Differential Privacy Prevent Label Inference Attacks? - Ruihan Wu; Jin Peng Zhou; Kilian Q. Weinberger; Chuan Guo 001 (AISTATS, 2023)

Learning To Invert: Simple Adaptive Attacks for Gradient Inversion in Federated Learning. - Ruihan Wu; Xiangyu Chen 007; Chuan Guo 001; Kilian Q. Weinberger (UAI, 2023)

Large-Scale Public Data Improves Differentially Private Image Generation Quality. - Ruihan Wu; Chuan Guo 001; Kamalika Chaudhuri (CoRR, 2023)

S-Taper Fiber Based Moisture Sensing in Power Transformer Oil. - Jun Jiang 005; Ruihan Wu; Jinfeng Liu; Xuerui Wu; Qiang Wu 005; Prem Ranjan; Xiaoqin Zhang 003; Jun Liu (IEEE Trans. Instrum. Meas., 2023)

Online Feature Updates Improve Online (Generalized) Label Shift Adaptation. - Ruihan Wu; Siddhartha Datta; Yi Su; Dheeraj Baby; Yu-Xiang Wang 003; Kilian Q. Weinberger (NeurIPS, 2024)

The binding pattern of ferric iron and iron-binding protein in Botrytis cinerea. - Ruihan Wu; Donglin Xie; Juan Du 003 (Comput. Biol. Medicine, 2024)

Better Membership Inference Privacy Measurement through Discrepancy. - Ruihan Wu; Pengrun Huang; Kamalika Chaudhuri (CoRR, 2024)

Influence-based Attributions can be Manipulated. - Chhavi Yadav; Ruihan Wu; Kamalika Chaudhuri (CoRR, 2024)

Evaluating Deep Unlearning in Large Language Models. - Ruihan Wu; Chhavi Yadav; Russ Salakhutdinov; Kamalika Chaudhuri (CoRR, 2024)

Privacy-Preserving Retrieval Augmented Generation with Differential Privacy. - Tatsuki Koga; Ruihan Wu; Kamalika Chaudhuri (CoRR, 2024)

MRME-Net: Towards multi-semantics learning and long-tail problem of efficient event detection from social messages. - Ruihan Wu; Tianfa Hong; Fangying Wan (J. King Saud Univ. Comput. Inf. Sci., 2024)

Large Scale Knowledge Washing. - Yu Wang 170; Ruihan Wu; Zexue He; Xiusi Chen; Julian J. McAuley (ICLR, 2025)

On Speeding Up Language Model Evaluation. - Jin Peng Zhou; Christian K. Belardi; Ruihan Wu; Travis Zhang; Carla P. Gomes; Wen Sun 002; Kilian Q. Weinberger (ICLR, 2025)

New Rates in Stochastic Decision-Theoretic Online Learning under Differential Privacy. - Ruihan Wu; Yu-Xiang Wang (CoRR, 2025)

Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness. - Rongzhe Wei; Peizhi Niu; Hans Hao-Hsun Hsu; Ruihan Wu; Haoteng Yin; Mohsen Ghassemi; Yifan Li; Vamsi K. Potluru; Eli Chien; Kamalika Chaudhuri; Olgica Milenkovic; Pan Li 005 (CoRR, 2025)

Can We Infer Confidential Properties of Training Data from LLMs? - Pengrun Huang; Chhavi Yadav; Ruihan Wu; Kamalika Chaudhuri (CoRR, 2025)

Learning-Time Encoding Shapes Unlearning in LLMs. - Ruihan Wu; Konstantin Garov; Kamalika Chaudhuri (CoRR, 2025)