Quoc V. Le


Notes

  • My new email: someone@somewhere where someone is quocle and somewhere is stanford.edu

    People
  • Yasemin Altun
  • Christopher J.C. Burges
  • Tiberio Caetano
  • Thomas Gärtner
  • Novi Quadrianto
  • Tim Sears
  • Alex Smola
  • Le Song
  • Choon Hui Teo
  • S V N Vishwanathan
  • Markus Weimer
  • Xinhua Zhang

    Publications: (Almost complete bibfile)

  • N. Quadrianto, A. J. Smola, T. S. Caetano, Q. V. Le.
    Estimating Labels from Label Proportions. ICML, 2008. [PDF]
    Topics: Gaussian Process classification, transduction, semi-supervised learning, prior knowledge.

  • M. Weimer, A. Karatzoglou, Q.V. Le, A.J. Smola.
    COFI RANK - Maximum Margin Matrix Factorization for Collaborative Ranking. NIPS 20, 2008. [PDF]
    Topics: ranking, collaborative-filtering, structured outputs, optimization.

  • A.J. Smola, S.V.N. Vishwanathan, Q.V. Le.
    Bundle methods for machine learning. NIPS 20, 2008. [PDF] [Appendix] [NIPS spotlight]
    Topics: optimization, theory.

  • O. Chapelle, Q.V. Le, A.J. Smola.
    Large margin optimization of ranking measures. NIPS Workshop: Machine Learning for Web Search, 2007. [PDF]
    Topics: ranking, structured outputs.

  • Q.V. Le, A.J. Smola.
    Direct optimization or ranking measures. NICTA Tech report, 2007. [PDF]
    Topics: ranking, structured outputs.

  • T. Caetano, L. Cheng, Q.V. Le, A.J. Smola.
    Learning graph matching. ICCV, 2007. [PDF] [Oral presentation].
    Topics: graph matching, max-margin structured outputs, vision.

  • C.H. Teo, Q.V. Le, A.J. Smola, SVN Vishwanathan.
    A Scalable Modular Convex Solver for Regularized Risk Minimization. KDD, 2007. [PDF], [Code]
    Topics: large-scale optimization, open-source software.

  • Q. V. Le, A. J. Smola, T. Gärtner, Y. Altun.
    Transductive Gaussian Process Regression with Automatic Model Selection. ECML, 2006. Best paper award.
    Topics: Gaussian Process regression, transduction.

  • C. Burges, R. Ragno, Q. V. Le.
    Learning to Rank with nonsmooth cost functions. NIPS 19, 2007. [PDF]
    Topics: ranking, neural networks.

  • Q. V. Le, A. J. Smola, T. Gärtner.
    Simpler knowledge-based Support Vector Machines. ICML, 2006. [PDF]
    Topics: prior knowledge, non-convex optimization.

  • T. Gärtner, Q. V. Le, S. Burton, A. J. Smola, S. V. N. Vishwanathan.
    Large-Scale Multiclass Transduction. NIPS 18, 2006. [PDF]
    Topics: Gaussian Process classification, multiclass, transduction.

  • Q. V. Le, A. J. Smola, S. Canu.
    Heteroscedastic Gaussian Process Regression. ICML, 2005. [PDF]
    Topics: Gaussian Process regression.

  • I. Takeuchi, Q. V. Le, T. Sears, A. J. Smola.
    Nonparametric quantile estimation. JMLR 7, 2006. [old PDF], [PDF]
    Topics: quantile estimation, median estimation, theory.

  • Q. V. Le, T. Sears, A. J. Smola.
    Nonparametric quantile estimation. NICTA Technical report, 2005. [PDF]
    Topics: quantile estimation, median estimation, theory.

  • T. Gärtner, T. Horvath, Q. V. Le, A. J. Smola, S. Wrobel.
    Kernel Methods for Graphs. Mining Graph Data. L. Holder, D. Cook (editors), 2005.
    Topics: Gaussian Process classification, graphs.

  • T. Gärtner, Q. V. Le, A. J. Smola.
    A Short Tour of Kernel Methods for Graphs. Tech report. 2006. [PDF]
    Topics: Gaussian Process classification, graphs.

    Talks
  • ICML 2006
  • ICML 2005

    Software
  • Some code is in ELEFANT.
  • Some other is in BMRM (mostly ChoonHui's work).

    Links
  • SML, National ICT Australia
  • Department of Computer Science,the ANU
  • kernel-machines.org
  • numarray manual and cvxopt

    Misc
  • This site has a lot of stories in Vietnamese.
  • Me at Kioloa.
  • A dramatic picture of me drawn by some famous person.










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