11 citations · 51 across the 24 of their papers we have counts for
4 papers · 1 filter
Decision-Focused Sequential Experimental Design: A Directional Uncertainty-Guided Approach
Beichen Wan, Mo Liu, Paul Grigas +1
We consider the sequential experimental design problem in the predict-then-optimize paradigm. In this paradigm, the outputs of the prediction model are used as coefficient vectors…
Binary Classification with Instance and Label Dependent Label Noise
Hyungki Im, Paul Grigas
Learning with label dependent label noise has been extensively explored in both theory and practice; however, dealing with instance (i.e., feature) and label dependent label noise…
Integrated Conditional Estimation-Optimization
Meng Qi, Paul Grigas, Zuo-Jun Max Shen
Many real-world optimization problems involve uncertain parameters with probability distributions that can be estimated using contextual feature information. In contrast to the sta…
AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods
Robert M. Freund, Paul Grigas, Rahul Mazumder
Boosting methods are highly popular and effective supervised learning methods which combine weak learners into a single accurate model with good statistical performance. In this pa…