Kernel Logistic Regression and the Import Vector Machine. - Ji Zhu 001; Trevor Hastie (NIPS, 2001)

Support Vector Machines, Kernel Logistic Regression and Boosting. - Ji Zhu 001; Trevor Hastie (Multiple Classifier Systems, 2002)

Boosting and support vector machines as optimal separators. - Saharon Rosset; Ji Zhu 001; Trevor Hastie (DRR, 2003)

Margin Maximizing Loss Functions. - Saharon Rosset; Ji Zhu 001; Trevor Hastie (NIPS, 2003)

1-norm Support Vector Machines. - Ji Zhu 001; Saharon Rosset; Trevor Hastie; Robert Tibshirani (NIPS, 2003)

The Entire Regularization Path for the Support Vector Machine. - Trevor Hastie; Saharon Rosset; Robert Tibshirani; Ji Zhu 001 (NIPS, 2004)

A Method for Inferring Label Sampling Mechanisms in Semi-Supervised Learning. - Saharon Rosset; Ji Zhu 001; Hui Zou; Trevor Hastie (NIPS, 2004)

Boosting as a Regularized Path to a Maximum Margin Classifier. - Saharon Rosset; Ji Zhu 001; Trevor Hastie (J. Mach. Learn. Res., 2004)

On Consistency of Community Detection in Networks - Yunpeng Zhao; Elizaveta Levina; Ji Zhu 001 (CoRR, 2011)

Sparse Ising Models with Covariates - Jie Cheng; Elizaveta Levina; Pei Wang; Ji Zhu 001 (CoRR, 2012)

Link prediction for partially observed networks - Yunpeng Zhao; Elizaveta Levina; Ji Zhu 001 (CoRR, 2013)

Community Detection in Networks with Node Features. - Yuan Zhang; Elizaveta Levina; Ji Zhu 001 (CoRR, 2015)

Link prediction for egocentrically sampled networks. - Yun-Jhong Wu; Elizaveta Levina; Ji Zhu 001 (CoRR, 2018)

High-dimensional Gaussian graphical model for network-linked data. - Tianxi Li; Cheng Qian; Elizaveta Levina; Ji Zhu 001 (CoRR, 2019)

High-dimensional Gaussian graphical models on network-linked data. - Tianxi Li; Cheng Qian; Elizaveta Levina; Ji Zhu 001 (J. Mach. Learn. Res., 2020)

Detecting Overlapping Communities in Networks Using Spectral Methods. - Yuan Zhang; Elizaveta Levina; Ji Zhu 001 (SIAM J. Math. Data Sci., 2020)

Fair Information Spread on Social Networks with Community Structure. - Octavio Mesner; Elizaveta Levina; Ji Zhu 001 (CoRR, 2023)

Link Prediction for Egocentrically Sampled Networks. - Tianxi Li; Yun-Jhong Wu; Elizaveta Levina; Ji Zhu 001 (J. Comput. Graph. Stat., 2023)

Community models for networks observed through edge nominations. - Tianxi Li; Elizaveta Levina; Ji Zhu 001 (J. Mach. Learn. Res., 2023)

General linear threshold models with application to influence maximization. - Alexander Kagan; Elizaveta Levina; Ji Zhu 001 (CoRR, 2024)

Variational Estimators of the Degree-corrected Latent Block Model for Bipartite Networks. - Yunpeng Zhao; Ning Hao; Ji Zhu 001 (J. Mach. Learn. Res., 2024)