Talks & Conference Presentations

  • Optimal Sparse Designs for General Process Flexibility , 09/2016
    The University of Illinois at Urbana-Champaign, Urbana, IL.
  • Testing Independence with High-dimensional Correlated Samples , 06/2016
    Joint Statistical Meetings, Chicago, IL.
  • Bayesian Dynamic Learning and Pricing with Strategic Customers , 06/2016
    INFORMS Revenue Management and Pricing Section Conference, New York, NY.
  • Testing Independence with High-dimensional Correlated Samples , 06/2016
    International Chinese Statistical Association (ICSA) Applied Statistical Symposium, Atlanta, GA.
  • Statistical Estimation and Sequential Analysis for Crowdsourcing , 06/2016
    Conference on Statistical Learning and Data Science, University of North Carolina at Chapel Hill, NC.
  • Bayesian Dynamic Learning and Pricing with Strategic Customers , 03/2016
    Informs Optimization Society Conference, Princeton, NJ.
  • Statistical Estimation and Sequential Analysis for Crowdsourcing , 06/2016
    Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, China.
  • Statistical Estimation and Decision-making for Crowdsourcing , 11/2015
    Wilks Statistics Seminar, Princeton University, Princeton, NJ.
  • A Statistical Learning Approach to Personalization in Revenue Management , 11/2015
    IOMS Colloquium, Stern School of Business, New York, NY.
  • Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing , 07/2015
    IMS-China International Conference on Statistics and Probability, Kunming, China
  • Spectral Methods meet EM: A Provably Optimal Algorithm for Crowdsourcing , 06/2015
    New Researchers Conference on High-Dimensional Statistics in the Age of Big Data, Beijing, China
  • Statistical Estimation and Decision-making for Crowdsourcing , 02/2015
    Columbia University, NY
  • Lower Bounds on the Bayes Risk and Minimax Risk , 12/2014
    Simons Institute for the Theory of Computing, UC Berkeley, CA
  • Lower Bounds on the Bayes Risk and Minimax Risk , 10/2014
    Allerton Conference, IL
  • Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders, 06/2014
    MSOM Conference, Seattle, WA.
  • Statistical Decision Making for Optimal Budget Allocation in Crowdsourcing, 03/2014
    Google Research at Mountain View, CA.
  • Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders, 02/2014
    UC Berkeley, CA.
  • Optimal Sparse Designs for Process Flexibility via Probabilistic Expanders, 02/2014
    Duke University, NC.
  • Statistical Decision Making for Optimal Budget Allocation in Crowdsourcing, 01/2014
    Data Science Seminar, Stanford University, CA.
  • Statistical Decision Making for Optimal Budget Allocation in Crowdsourcing, 10/2013
    Informs Annual Meeting, MN.
  • Statistical Decision Making for Optimal Budget Allocation in Crowdsourcing, 04/2013
    Microsoft Research at New York, NY.
  • Uniformly-optimal Stochastic Dual Averaging Methods with Double Projections, 10/2012
    Informs Annual Meeting, AZ.
  • Optimal Budget Allocation in Crowdsourcing, 10/2012
    Microsoft Research Redmond, WA.
  • Predicting Consensus Ranking in Crowdsourced Setting, 07/2012
    Microsoft Research Redmond, WA.
  • Structured Sparse Canonical Correlation Analysis, 04/2012
    International Conference on Artificial Intelligence and Statistics (AISTATS).
  • Optimization for General Structured Sparse Learning, 03/2012
    Microsoft Research Redmond, WA.
  • Sparse Learning for Text Mining, 12/2011
    Microsoft Research Aisa, Beijing, China.
  • Graph-Valued Regression, 08/2011
    NEC Lab American, NJ.
  • Proximal Gradient Descent for Structured Sparse Learning, 08/2010
    Princeton University, NJ.
  • Multivariate Dyadic Regression Trees for Sparse Learning Problems, 08/2010
    Joint Statistical Meeting 2010, Vancouver, Canada.
  • Proximal Gradient Descent for Structured Sparse Learning, 07/2010
    University of British Columbia, Vancouver, Canada.
  • Proximal Gradient Descent for Structured Sparse Learning, 07/2010
    IBM Thomas J. Watson Research Center, NY.
  • Accelerated Gradient Method for Multi-Task Sparse Learning Problem 12/2009
    • International Conference on Data Mining (ICDM).


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