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Journal Articles
- 2023
[j5]Othman El Balghiti, Adam N. Elmachtoub
, Paul Grigas, Ambuj Tewari:
Generalization Bounds in the Predict-Then-Optimize Framework. Math. Oper. Res. 48(4): 2043-2065 (2023)- [j4]Meng Li, Paul Grigas, Alper Atamtürk:
On the softplus penalty for large-scale convex optimization. Oper. Res. Lett. 51(6): 666-672 (2023) - 2022
- [j3]Adam N. Elmachtoub, Paul Grigas:
Smart "Predict, then Optimize". Manag. Sci. 68(1): 9-26 (2022) - 2017
- [j2]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): 319-346 (2017) - 2016
- [j1]Robert M. Freund, Paul Grigas:
New analysis and results for the Frank-Wolfe method. Math. Program. 155(1-2): 199-230 (2016)
Conference and Workshop Papers
- 2021
- [c4]Alfonso Lobos, Paul Grigas, Zheng Wen:
Joint Online Learning and Decision-making via Dual Mirror Descent. ICML 2021: 7080-7089 - [c3]Heyuan Liu, Paul Grigas:
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method. NeurIPS 2021: 22083-22094 - 2019
- [c2]Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari:
Generalization Bounds in the Predict-then-Optimize Framework. NeurIPS 2019: 14389-14398 - 2017
- [c1]Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-chih Lee:
Profit Maximization for Online Advertising Demand-Side Platforms. ADKDD@KDD 2017: 11:1-11:7
Informal and Other Publications
- 2023
- [i13]Mo Liu, Paul Grigas, Heyuan Liu, Zuo-Jun Max Shen:
Active Learning in the Predict-then-Optimize Framework: A Margin-Based Approach. CoRR abs/2305.06584 (2023) - [i12]Hyungki Im, Paul Grigas:
Binary Classification with Instance and Label Dependent Label Noise. CoRR abs/2306.03402 (2023) - 2022
- [i11]Heyuan Liu, Paul Grigas:
Online Contextual Decision-Making with a Smart Predict-then-Optimize Method. CoRR abs/2206.07316 (2022) - 2021
- [i10]Alfonso Lobos, Paul Grigas, Zheng Wen:
Joint Online Learning and Decision-making via Dual Mirror Descent. CoRR abs/2104.09750 (2021) - [i9]Heyuan Liu, Paul Grigas:
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method. CoRR abs/2108.08887 (2021) - [i8]Paul Grigas, Meng Qi, Zuo-Jun Shen:
Integrated Conditional Estimation-Optimization. CoRR abs/2110.12351 (2021) - 2019
- [i7]Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari:
Generalization Bounds in the Predict-then-Optimize Framework. CoRR abs/1905.11488 (2019) - [i6]Paul Grigas, Alfonso Lobos, Nathan Vermeersch:
Stochastic In-Face Frank-Wolfe Methods for Non-Convex Optimization and Sparse Neural Network Training. CoRR abs/1906.03580 (2019) - 2018
- [i5]Robert M. Freund, Paul Grigas, Rahul Mazumder:
Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods. CoRR abs/1810.08727 (2018) - 2017
- [i4]Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-chih Lee:
Profit Maximization for Online Advertising Demand-Side Platforms. CoRR abs/1706.01614 (2017) - [i3]Adam N. Elmachtoub, Paul Grigas:
Smart "Predict, then Optimize". CoRR abs/1710.08005 (2017) - 2015
- [i2]Robert M. Freund, Paul Grigas, Rahul Mazumder:
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives. CoRR abs/1505.04243 (2015) - 2013
- [i1]Robert M. Freund, Paul Grigas, Rahul Mazumder:
AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods. CoRR abs/1307.1192 (2013)
Coauthor Index
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