NIPS Proceedingsβ

Rong Jin

23 Papers

  • Extracting Certainty from Uncertainty: Transductive Pairwise Classification from Pairwise Similarities (2014)
  • Top Rank Optimization in Linear Time (2014)
  • Linear Convergence with Condition Number Independent Access of Full Gradients (2013)
  • Mixed Optimization for Smooth Functions (2013)
  • Speedup Matrix Completion with Side Information: Application to Multi-Label Learning (2013)
  • Stochastic Convex Optimization with Multiple Objectives (2013)
  • Nyström Method vs Random Fourier Features: A Theoretical and Empirical Comparison (2012)
  • Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning (2012)
  • Stochastic Gradient Descent with Only One Projection (2012)
  • Active Learning by Querying Informative and Representative Examples (2010)
  • Multi-label Multiple Kernel Learning by Stochastic Approximation: Application to Visual Object Recognition (2010)
  • Adaptive Regularization for Transductive Support Vector Machine (2009)
  • DUOL: A Double Updating Approach for Online Learning (2009)
  • Learning Bregman Distance Functions and Its Application for Semi-Supervised Clustering (2009)
  • Learning to Rank by Optimizing NDCG Measure (2009)
  • Regularized Distance Metric Learning:Theory and Algorithm (2009)
  • An Extended Level Method for Efficient Multiple Kernel Learning (2008)
  • Multi-label Multiple Kernel Learning (2008)
  • Semi-supervised Learning with Weakly-Related Unlabeled Data : Towards Better Text Categorization (2008)
  • Efficient Convex Relaxation for Transductive Support Vector Machine (2007)
  • Generalized Maximum Margin Clustering and Unsupervised Kernel Learning (2006)
  • A Probabilistic Approach for Optimizing Spectral Clustering (2005)
  • Learning with Multiple Labels (2002)