Publications

 Robust Optimisation and Discrete Choice:
  1. S D Ahipasaoglu, U Arikan, and K Natarajan. On the Flexibility of using Marginal Distribution Choice Models in Traffic Equilibrium, Transportation Research Part B: Methodological, (91) 130-158, 2016. [pdf]
  2. S D Ahipasaoglu, R Meskarian, T Magnanti, and K Natarajan. Beyond Normality: A Distributionally Robust Stochastic User Equilibrium Model, Transportation Research Part B: Methodological, (81) 331-654, 2015. [pdf]
  3. S D Ahipasaoglu, X Li, K Natarajan. A Convex Optimization Approach for Computing Correlated Choice Probabilities with Many Alternatives. (under review) [pdf]
  4. Y Yang, S D Ahipasaoglu, and J Chen. Worst-Case and Sparse Portfolio Selection: Insights and Alternatives. (under review, Finalist in 2016 Informs FSS Best Student Paper Competition.) [pdf]
  5. S D Ahipasaoglu, K Natarajan, and D Shi. Distributionally Robust Project Crashing with Partial or No Correlation Information.  (under review) [pdf]
Optimal Experimental Design:
  1. S D Ahipasaoglu. Fast Algorithms for the Minimum Volume Estimator, Journal of Global Optimisation, (62) 351-370, 2015. [pdf]
  2. S D Ahipasaoglu. A First-Order Algorithm for the A-Optimal Experimental Design Problem, Statistics and Computing, (25) 1113-1127, 2015. [pdf]
  3. S D Ahipasaoglu and M J Todd. A Modifi ed Frank-Wolfe Algorithm for Computing Minimum-Area Enclosing Ellipsoidal Cylinders: Theory and Algorithms, Computational Geometry: Theory and Applications, (46) 494-519, 2013. [pdf]
  4. S D Ahipasaoglu and E A Yildirim. Identi cation and Elimination of Interior Points for the Minimum Enclosing Ball Problem. SIAM Journal on Optimization, (19) 1392-1396, 2008. [pdf]
  5. S D Ahipasaoglu, P Sun, and M J Todd. Linear Convergence of a Modi ed Frank-Wolfe Algorithm for Computing Minimum-Volume Enclosing Ellipsoids. Optimization Methods and Software, (23) 5-19, 2008. [pdf]
Statistical Learning:
  1. R Taormina, S Galelli, G Karakaya, S D Ahipasaoglu. An information theoretic approach to select alternate subsets of predictors for data-driven hydrological models. Journal of Hydrology, in press.
  2. G Karakaya, S Galelli, S D Ahipasaoglu, and R Taormina. Identifying (quasi) equally informative subsets in feature selection problems for classification: a max-relevance min-redundancy approach. IEEE Transactions on Cybernetics,  (46) 1424-1437, 2016. [pdf]
  3. M Takac, S D Ahipasaoglu, N-M Cheung, and P Richtarik. TOP-SPIN: Topic Discovery via Sparse PCA Interference, 2014. [pdf]
  4. Richtarik, P., Takac, M., and S D Ahipasaoglu. 24 Parallel Codes for Sparse PCA, 2014. [pdf]
  5. F Bach, S D Ahipasaoglu, and A d’Aspremont. Convex Relaxations for Subset Selection, 2010. [pdf]
  6. V Krishnamurthy, S D Ahipasaoglu, and A d’Aspremont. A Pathwise Algorithm for Covariance Selection. Optimization for Machine Learning. (Eds.) Sra, S., S. Nowozin, S. J. Wright, MIT Press, Cambridge, MA, USA, 2011.
Energy Management on Smart Grids:
  1. T Wang, Y Xu, S D Ahipasaoglu, and C Courcoubetis. Ex-post Max-min Fairness of Generalized AGV Mechanisms, IEEE Transactions on Automatic Control, in press.
  2. C Bo, A Costa, S D Ahipasaoglu, C Yuen, Y Zaiyue. Optimal Meeting Scheduling in Smart Commercial Buildings for Energy Cost Reduction. IEEE Transactions on Smart Grid, in press.
  3. T Wang, Y Xu, C Withanage, L Lan, S D Ahipasaoglu, and C Courcubetis. A Fair and Budget-Balanced Incentive Mechanism for Energy Management in Buildings, IEEE Transactions on Smart Grid, in press.
  4. T Wang, Y Xu, S D Ahipasaoglu, and C Courcoubetis. €œA Fair Bayesian Incentive Compatible Mechanism€, 54th IEEE Conference on Decision and Control (CDC), Osaka, Dec 2015.
  5. C Bo, A Costa, S D Ahipasaoglu, S Huang, C Yuen, Y Zaiyue. Minimizing Commercial Building Cost in Smart Grid: An Optimal Meeting Scheduling Approach. IEEE International Conference on Smart Grid Communications (SmartGridComm), Venice, Nov 2014.