NIPS Proceedingsβ

Jun Zhu

9 Papers

  • Learning From Weakly Supervised Data by The Expectation Loss SVM (e-SVM) algorithm (2014)
  • Monte Carlo Methods for Maximum Margin Supervised Topic Models (2012)
  • Nonparametric Max-Margin Matrix Factorization for Collaborative Prediction (2012)
  • Infinite Latent SVM for Classification and Multi-task Learning (2011)
  • Adaptive Multi-Task Lasso: with Application to eQTL Detection (2010)
  • Efficient Relational Learning with Hidden Variable Detection (2010)
  • Large Margin Learning of Upstream Scene Understanding Models (2010)
  • Predictive Subspace Learning for Multi-view Data: a Large Margin Approach (2010)
  • Partially Observed Maximum Entropy Discrimination Markov Networks (2008)