On the fundamental statistical limit of community detection in random hypergraphs. - Chung-Yi Lin; I (Eli) Chien; I-Hsiang Wang (ISIT, 2017)

Community Detection in Hypergraphs: Optimal Statistical Limit and Efficient Algorithms. - I (Eli) Chien; Chung-Yi Lin; I-Hsiang Wang (AISTATS, 2018)

Query K-means Clustering and the Double Dixie Cup Problem. - I (Eli) Chien; Chao Pan 003; Olgica Milenkovic (NeurIPS, 2018)

HS2: Active Learning over Hypergraphs. - I (Eli) Chien; Huozhi Zhou; Pan Li 005 (CoRR, 2018)

HS2: Active learning over hypergraphs with pointwise and pairwise queries. - I (Eli) Chien; Huozhi Zhou; Pan Li 005 (AISTATS, 2019)

Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection. - Pan Li 005; I (Eli) Chien; Olgica Milenkovic (NeurIPS, 2019)

Support Estimation via Regularized and Weighted Chebyshev Approximations. - I (Eli) Chien; Olgica Milenkovic (CoRR, 2019)

On the Minimax Misclassification Ratio of Hypergraph Community Detection. - I Eli Chien; Chung-Yi Lin; I-Hsiang Wang (IEEE Trans. Inf. Theory, 2019)

Active Learning in the Geometric Block Model. - Eli Chien; Antonia M. Tulino; Jaime Llorca (AAAI, 2020)

Multi-MotifGAN (MMGAN): Motif-Targeted Graph Generation And Prediction. - Anuththari Gamage; Eli Chien; Jianhao Peng; Olgica Milenkovic (ICASSP, 2020)

Joint Adaptive Feature Smoothing and Topology Extraction via Generalized PageRank GNNs. - Eli Chien; Jianhao Peng; Pan Li 005; Olgica Milenkovic (CoRR, 2020)

Highly Scalable and Provably Accurate Classification in Poincaré Balls. - Eli Chien; Chao Pan 003; Puoya Tabaghi; Olgica Milenkovic (ICDM, 2021)

Adaptive Universal Generalized PageRank Graph Neural Network. - Eli Chien; Jianhao Peng; Pan Li 005; Olgica Milenkovic (ICLR, 2021)

Support Estimation with Sampling Artifacts and Errors. - Eli Chien; Olgica Milenkovic; Angelia Nedich (ISIT, 2021)

Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs. - Eli Chien; Pan Li 005; Olgica Milenkovic (ITW, 2021)

Linear Classifiers in Mixed Constant Curvature Spaces. - Puoya Tabaghi; Eli Chien; Chao Pan 003; Olgica Milenkovic (CoRR, 2021)

Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction. - Eli Chien; Wei-Cheng Chang; Cho-Jui Hsieh; Hsiang-Fu Yu; Jiong Zhang; Olgica Milenkovic; Inderjit S. Dhillon (ICLR, 2022)

You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks. - Eli Chien; Chao Pan 003; Jianhao Peng; Olgica Milenkovic (ICLR, 2022)

HyperAid: Denoising in Hyperbolic Spaces for Tree-fitting and Hierarchical Clustering. - Eli Chien; Puoya Tabaghi; Olgica Milenkovic (KDD, 2022)

Certified Graph Unlearning. - Eli Chien; Chao Pan 003; Olgica Milenkovic (CoRR, 2022)

Unlearning Nonlinear Graph Classifiers in the Limited Training Data Regime. - Chao Pan 003; Eli Chien; Olgica Milenkovic (CoRR, 2022)

Efficient Model Updates for Approximate Unlearning of Graph-Structured Data. - Eli Chien; Chao Pan 003; Olgica Milenkovic (ICLR, 2023)

PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation. - Eli Chien; Jiong Zhang; Cho-Jui Hsieh; Jyun-Yu Jiang; Wei-Cheng Chang; Olgica Milenkovic; Hsiang-Fu Yu (ICML, 2023)

Representer Point Selection for Explaining Regularized High-dimensional Models. - Che-Ping Tsai; Jiong Zhang; Hsiang-Fu Yu; Eli Chien; Cho-Jui Hsieh; Pradeep Kumar Ravikumar (ICML, 2023)

Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. - Eli Chien; Wei-Ning Chen; Chao Pan 003; Pan Li 005; Ayfer Özgür; Olgica Milenkovic (NeurIPS, 2023)

Unlearning Graph Classifiers with Limited Data Resources. - Chao Pan 003; Eli Chien; Olgica Milenkovic (WWW, 2023)

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. - Rongzhe Wei; Eleonora Kreacic; Haoyu Wang 004; Haoteng Yin; Eli Chien; Vamsi K. Potluru; Pan Li 005 (CoRR, 2023)

Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning. - Zheyuan Liu 010; Guangyao Dou; Yijun Tian 001; Chunhui Zhang; Eli Chien; Ziwei Zhu 001 (CoRR, 2023)

Small-Sample Estimation of the Mutational Support and Distribution of SARS-CoV-2. - Vishal Rana; Eli Chien; Jianhao Peng; Olgica Milenkovic (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Provably accurate and scalable linear classifiers in hyperbolic spaces. - Chao Pan 003; Eli Chien; Puoya Tabaghi; Jianhao Peng; Olgica Milenkovic (Knowl. Inf. Syst., 2023)

Machine Unlearning of Pre-trained Large Language Models. - Jin Yao; Eli Chien; Minxin Du; Xinyao Niu; Tianhao Wang 001; Zezhou Cheng; Xiang Yue (ACL (1), 2024)

Certified Machine Unlearning via Noisy Stochastic Gradient Descent. - Eli Chien; Haoyu Wang 004; Ziang Chen; Pan Li 005 (NeurIPS, 2024)

Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning. - Eli Chien; Haoyu Wang 004; Ziang Chen; Pan Li 005 (NeurIPS, 2024)

Differentially Private Graph Diffusion with Applications in Personalized PageRanks. - Rongzhe Wei; Eli Chien; Pan Li 005 (NeurIPS, 2024)

Breaking the Trilemma of Privacy, Utility, and Efficiency via Controllable Machine Unlearning. - Zheyuan Liu 010; Guangyao Dou; Eli Chien; Chunhui Zhang; Yijun Tian 001; Ziwei Zhu 001 (WWW, 2024)

Stochastic Gradient Langevin Unlearning. - Eli Chien; Haoyu Wang 004; Ziang Chen; Pan Li 005 (CoRR, 2024)

Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. - Haoteng Yin; Rongzhe Wei; Eli Chien; Pan Li 005 (CoRR, 2024)

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. - Mufei Li; Viraj Shitole; Eli Chien; Changhai Man; Zhaodong Wang; Srinivas Sridharan 002; Ying Zhang; Tushar Krishna; Pan Li 005 (CoRR, 2024)

Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning. - Rongzhe Wei; Mufei Li; Mohsen Ghassemi; Eleonora Kreacic; Yifan Li; Xiang Yue; Bo Li; Vamsi K. Potluru; Pan Li 005; Eli Chien (CoRR, 2024)

Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls. - Saurav Prakash; Jin Sima; Chao Pan 003; Eli Chien; Olgica Milenkovic (Trans. Mach. Learn. Res., 2024)

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. - Rongzhe Wei; Eleonora Kreacic; Haoyu Peter Wang; Haoteng Yin; Eli Chien; Vamsi K. Potluru; Pan Li 005 (Trans. Mach. Learn. Res., 2024)

Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness. - Eli Chien; Pan Li 005 (ICLR, 2025)

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. - Mufei Li; Viraj Shitole; Eli Chien; Changhai Man; Zhaodong Wang; Srinivas; Ying Zhang; Tushar Krishna; Pan Li 005 (ICLR, 2025)

Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States. - Eli Chien; Wei-Ning Chen; Pan Li 005 (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)

Differentially Private Relational Learning with Entity-level Privacy Guarantees. - Yinan Huang; Haoteng Yin; Eli Chien; Rongzhe Wei; Pan Li 005 (CoRR, 2025)