Solving stochastic and bilevel mixed-integer programs via a generalized value function O Tavaslıoğlu, OA Prokopyev, AJ Schaefer Operations Research 67 (6), 1659-1677, 2019 | 21 | 2019 |
On the structure of the inverse-feasible region of a linear program O Tavaslıoğlu, T Lee, S Valeva, AJ Schaefer Operations Research Letters 46 (1), 147-152, 2018 | 21 | 2018 |
Shallow univariate ReLu networks as splines: initialization, loss surface, Hessian, and gradient flow dynamics J Sahs, R Pyle, A Damaraju, JO Caro, O Tavaslioglu, A Lu, F Anselmi, ... Frontiers in artificial intelligence 5, 889981, 2022 | 15 | 2022 |
Reinforcement learning of simplex pivot rules: a proof of concept V Suriyanarayana, O Tavaslıoğlu, AB Patel, AJ Schaefer Optimization Letters 16 (8), 2513-2525, 2022 | 3 | 2022 |
A functional characterization of randomly initialized gradient descent in deep relu networks J Sahs, A Damaraju, R Pyle, O Tavaslioglu, JO Caro, HY Lu, A Patel | 3 | 2019 |
DeepSimplex: Reinforcement Learning of Pivot Rules Improves the Efficiency of Simplex Algorithm in Solving Linear Programming Problems V Suriyanarayana, O Tavaslioglu, AB Patel, AJ Schaefer | 3 | 2019 |
Novel Method of Calculating Pulse Pressure Variation to Predict Fluid Responsiveness to Transfusion in Very Low Birth Weight Infants ZC Foughty, O Tavaslioglu, CJ Rhee, LI Elizondo, CG Rusin, DJ Penny, ... The Journal of pediatrics 234, 265-268. e1, 2021 | | 2021 |
Operating Room Scheduling and Integrated Block Assignments Under Emergency Arrivals O Tavaslioglu University of Pittsburgh, 2019 | | 2019 |
Optimal Policy Structure for Risk-Sensitive Airline Revenue Management O Tavaslıoğlu, ZM Avşar | | 2013 |
Risk-Sensitive Models for Airline Network Revenue Management O Tavaslıoğlu, ZM Avşar | | 2013 |