224 citations · 3.2k across the 170 of their papers we have counts for
4 papers · 1 filter
Online Bayesian Passive-Aggressive Learning
Tianlin Shi, Jun Zhu
Online Passive-Aggressive (PA) learning is an effective framework for performing max-margin online learning. But the deterministic formulation and estimated single large-margin mod…
Gibbs Max-margin Topic Models with Data Augmentation
Jun Zhu, Ning Chen, Hugh Perkins +1
Max-margin learning is a powerful approach to building classifiers and structured output predictors. Recent work on max-margin supervised topic models has successfully integrated i…
Discriminative Relational Topic Models
Ning Chen, Jun Zhu, Fei Xia +1
Many scientific and engineering fields involve analyzing network data. For document networks, relational topic models (RTMs) provide a probabilistic generative process to describe…
Improved Bayesian Logistic Supervised Topic Models with Data Augmentation
Jun Zhu, Xun Zheng, Bo Zhang
Supervised topic models with a logistic likelihood have two issues that potentially limit their practical use: 1) response variables are usually over-weighted by document word coun…