Invited Conference Presentations:


  • Derivative-Free AUC Optimization, Optimization Methods for the Next Generation of Machine Learning, ICML Conference, New York, NY, USA, June 2016.
  • Derivative-Free Optimization for Hyper-Parameter Tuning in Machine Learning Problems, Machine Learning Symposium, New York, NY, USA, March 2016.

CRA@L Lab Seminar Presentations:

  • Directly and Efficiently Optimizing Prediction Error and AUC of Linear Classifiers, Lehigh University, PA, USA, November 2017.
  • Proximal Quasi-Newton Methods for Convex Optimization, Lehigh University, PA, USA, September 2016.
  • Derivative-Free AUC Optimization, Lehigh University, PA, USA, April 2016.
  • Accelerated Proximal Quasi-Newton Algorithm to Solve Convex Composite Problems, Lehigh University, PA, USA, April 2015.