Paul Grigas

Publication Activity (10 Years)

Years Active: 2013-2023
Publications (10 Years): 21

Top Topics

Profit Maximization

Convex Optimization

Top Venues

Publications

Hyungki Im, Paul Grigas
Binary Classification with Instance and Label Dependent Label Noise. CoRR (2023)
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
Generalization Bounds in the Predict-Then-Optimize Framework. Math. Oper. Res. 48 (4) (2023)
Meng Li, Paul Grigas, Alper Atamtürk
On the softplus penalty for large-scale convex optimization. Oper. Res. Lett. 51 (6) (2023)
Mo Liu, Paul Grigas, Heyuan Liu, Zuo-Jun Max Shen
Active Learning in the Predict-then-Optimize Framework: A Margin-Based Approach. CoRR (2023)
Adam N. Elmachtoub, Paul Grigas
Smart "Predict, then Optimize". Manag. Sci. 68 (1) (2022)
Heyuan Liu, Paul Grigas
Online Contextual Decision-Making with a Smart Predict-then-Optimize Method. CoRR (2022)
Paul Grigas, Meng Qi, Zuo-Jun Shen
Integrated Conditional Estimation-Optimization. CoRR (2021)
Alfonso Lobos, Paul Grigas, Zheng Wen
Joint Online Learning and Decision-making via Dual Mirror Descent. ICML (2021)
Heyuan Liu, Paul Grigas
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method. CoRR (2021)
Alfonso Lobos, Paul Grigas, Zheng Wen
Joint Online Learning and Decision-making via Dual Mirror Descent. CoRR (2021)
Heyuan Liu, Paul Grigas
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method. NeurIPS (2021)
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
Generalization Bounds in the Predict-then-Optimize Framework. CoRR (2019)
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
Generalization Bounds in the Predict-then-Optimize Framework. NeurIPS (2019)
Paul Grigas, Alfonso Lobos, Nathan Vermeersch
Stochastic In-Face Frank-Wolfe Methods for Non-Convex Optimization and Sparse Neural Network Training. CoRR (2019)
Robert M. Freund, Paul Grigas, Rahul Mazumder
Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods. CoRR (2018)
Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-chih Lee
Profit Maximization for Online Advertising Demand-Side Platforms. CoRR (2017)
Adam N. Elmachtoub, Paul Grigas
Smart "Predict, then Optimize". CoRR (2017)
Robert M. Freund, Paul Grigas, Rahul Mazumder
An Extended Frank-Wolfe Method with "In-Face" Directions, and Its Application to Low-Rank Matrix Completion. SIAM J. Optim. 27 (1) (2017)
Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-chih Lee
Profit Maximization for Online Advertising Demand-Side Platforms. ADKDD@KDD (2017)
Robert M. Freund, Paul Grigas
New analysis and results for the Frank-Wolfe method. Math. Program. 155 (1-2) (2016)
Robert M. Freund, Paul Grigas, Rahul Mazumder
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives. CoRR (2015)
Robert M. Freund, Paul Grigas, Rahul Mazumder
AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods. CoRR (2013)