Paul Grigas

30 papers A* 3A 1Journal 24Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Decision-Focused Sequential Experimental Design: A Directional Uncertainty-Guided Approach.
CoRR
Beichen Wan, Mo Liu, Paul Grigas, Zuo-Jun Max Shen
2025 A conf
Beyond Discretization: Learning the Optimal Solution Path.
AISTATS
Qiran Dong, Paul Grigas, Vishal Gupta
2025 J jnl
New Methods for Parametric Optimization via Differential Equations.
SIAM J. Optim.
Heyuan Liu, Paul Grigas
2025 J jnl
New Penalized Stochastic Gradient Methods for Linearly Constrained Strongly Convex Optimization.
J. Optim. Theory Appl.
Meng Li, Paul Grigas, Alper Atamtürk
2025 J jnl
Self-Supervised Penalty-Based Learning for Robust Constrained Optimization.
CoRR
Wyame Benslimane, Paul Grigas
2025 — conf
Self-supervised Penalty-Based Learning for Robust Constrained Optimization.
CPAIOR (1)
Wyame Benslimane, Paul Grigas
2025 J jnl
Smart Surrogate Losses for Contextual Stochastic Linear Optimization with Robust Constraints.
CoRR
Hyungki Im, Wyame Benslimane, Paul Grigas
2025 J jnl
Stochastic First-Order Algorithms for Constrained Distributionally Robust Optimization.
INFORMS J. Comput.
Hyungki Im, Paul Grigas
2023 J jnl
Active Learning in the Predict-then-Optimize Framework: A Margin-Based Approach.
CoRR
Mo Liu, Paul Grigas, Heyuan Liu, Zuo-Jun Max Shen
2023 J jnl
Binary Classification with Instance and Label Dependent Label Noise.
CoRR
Hyungki Im, Paul Grigas
2023 J jnl
Generalization Bounds in the Predict-Then-Optimize Framework.
Math. Oper. Res.
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
2023 J jnl
On the softplus penalty for large-scale convex optimization.
Oper. Res. Lett.
Meng Li, Paul Grigas, Alper Atamtürk
2022 J jnl
Online Contextual Decision-Making with a Smart Predict-then-Optimize Method.
CoRR
Heyuan Liu, Paul Grigas
2022 J jnl
Smart "Predict, then Optimize".
Manag. Sci.
Adam N. Elmachtoub, Paul Grigas
2021 J jnl
Integrated Conditional Estimation-Optimization.
CoRR
Paul Grigas, Meng Qi, Zuo-Jun Shen
2021 A* conf
Joint Online Learning and Decision-making via Dual Mirror Descent.
ICML
Alfonso Lobos, Paul Grigas, Zheng Wen
2021 J jnl
Joint Online Learning and Decision-making via Dual Mirror Descent.
CoRR
Alfonso Lobos, Paul Grigas, Zheng Wen
2021 A* conf
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method.
NeurIPS
Heyuan Liu, Paul Grigas
2021 J jnl
Risk Bounds and Calibration for a Smart Predict-then-Optimize Method.
CoRR
Heyuan Liu, Paul Grigas
2019 A* conf
Generalization Bounds in the Predict-then-Optimize Framework.
NeurIPS
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
2019 J jnl
Generalization Bounds in the Predict-then-Optimize Framework.
CoRR
Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
2019 J jnl
Stochastic In-Face Frank-Wolfe Methods for Non-Convex Optimization and Sparse Neural Network Training.
CoRR
Paul Grigas, Alfonso Lobos, Nathan Vermeersch
2018 J jnl
Condition Number Analysis of Logistic Regression, and its Implications for Standard First-Order Solution Methods.
CoRR
Robert M. Freund, Paul Grigas, Rahul Mazumder
2017 J jnl
An Extended Frank-Wolfe Method with "In-Face" Directions, and Its Application to Low-Rank Matrix Completion.
SIAM J. Optim.
Robert M. Freund, Paul Grigas, Rahul Mazumder
2017 — conf
Profit Maximization for Online Advertising Demand-Side Platforms.
ADKDD@KDD
Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-Chih Lee
2017 J jnl
Profit Maximization for Online Advertising Demand-Side Platforms.
CoRR
Paul Grigas, Alfonso Lobos, Zheng Wen, Kuang-Chih Lee
2017 J jnl
Smart "Predict, then Optimize".
CoRR
Adam N. Elmachtoub, Paul Grigas
2016 J jnl
New analysis and results for the Frank-Wolfe method.
Math. Program.
Robert M. Freund, Paul Grigas
2015 J jnl
A New Perspective on Boosting in Linear Regression via Subgradient Optimization and Relatives.
CoRR
Robert M. Freund, Paul Grigas, Rahul Mazumder
2013 J jnl
AdaBoost and Forward Stagewise Regression are First-Order Convex Optimization Methods.
CoRR
Robert M. Freund, Paul Grigas, Rahul Mazumder