Artikel mit Open-Access-Mandaten - Andres GomezWeitere Informationen
Verfügbar: 24
Safe screening rules for l0-regression from perspective relaxations
A Atamturk, A Gómez
International conference on machine learning, 421-430, 2020
Mandate: US National Science Foundation, US Department of Energy, US Department of …
Strong formulations for quadratic optimization with M-matrices and indicator variables
A Atamtürk, A Gómez
Mathematical Programming 170, 141-176, 2018
Mandate: US Department of Defense
Submodularity in conic quadratic mixed 0-1 optimization
A Atamturk, A Gomez
Operations Research 68 (2), 609-630, 2017
Mandate: US National Science Foundation
Sparse and smooth signal estimation: Convexification of l0 formulations
A Atamturk, A Gomez, S Han
Journal of Machine Learning Research 22, 1-43, 2021
Mandate: US National Science Foundation, US Department of Defense
A mixed-integer fractional optimization approach to best subset selection
A Gomez, O Prokopyev
INFORMS Journal on Computing 33, 551-565, 2021
Mandate: US National Science Foundation
Ideal formulations for constrained convex optimization problems with indicator variables
L Wei, A Gómez, S Küçükyavuz
Mathematical Programming 192 (1), 57-88, 2022
Mandate: US National Science Foundation, US Department of Defense
On the convexification of constrained quadratic optimization problems with indicator variables
L Wei, A Gómez, S Küçükyavuz
International conference on integer programming and combinatorial …, 2020
Mandate: US National Science Foundation, US Department of Defense
Supermodularity and valid inequalities for quadratic optimization with indicators
A Atamtürk, A Gómez
Mathematical Programming 201 (1), 295-338, 2023
Mandate: US National Science Foundation, US Department of Defense
A graph-based decomposition method for convex quadratic optimization with indicators
P Liu, S Fattahi, A Gómez, S Küçükyavuz
Mathematical Programming 200 (2), 669-701, 2023
Mandate: US National Science Foundation, US Department of Defense
Outlier detection in time series via mixed-integer conic quadratic optimization
A Gómez
SIAM Journal on Optimization 31 (3), 1897-1925, 2021
Mandate: US National Science Foundation
Strong formulations for conic quadratic optimization with indicator variables
A Gomez
Mathematical Programming 188, 193-226, 2021
Mandate: US National Science Foundation
Fractional 0-1 Programs: Links between Mixed-integer Linear and Conic Quadratic Formulations
E Mehmanchi, A Gómez, OA Prokopyev
Journal of Global Optimization 75 (2), 273-339, 2019
Mandate: US National Science Foundation
Optimal robust classification trees
N Justin, S Aghaei, A Gomez, P Vayanos
The AAAI-22 Workshop on Adversarial Machine Learning and Beyond, 2021
Mandate: US National Science Foundation
Fractional 0–1 programming and submodularity
S Han, A Gómez, OA Prokopyev
Journal of Global Optimization 84 (1), 77-93, 2022
Mandate: US National Science Foundation
Comparing Solution Paths of Sparse Quadratic Minimization with a Stieltjes Matrix
Z He, S Han, A Gomez, Y Cui, JS Pang
Mathematical Programming, 2023
Mandate: US National Science Foundation, US Department of Defense
Learning optimal fair decision trees: Trade-offs between interpretability, fairness, and accuracy
N Jo, S Aghaei, J Benson, A Gomez, P Vayanos
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 181-192, 2023
Mandate: US National Science Foundation
Scalable inference of sparsely-changing Gaussian Markov random fields
S Fattahi, A Gomez
Advances in Neural Information Processing Systems 34, 6529-6541, 2021
Mandate: US National Science Foundation
Linear-step solvability of some folded concave and singly-parametric sparse optimization problems
A Gómez, Z He, JS Pang
Mathematical Programming 198 (2), 1339-1380, 2023
Mandate: US National Science Foundation, US Department of Defense
Three‐partition flow cover inequalities for constant capacity fixed‐charge network flow problems
A Atamtürk, A Gómez, S Küçükyavuz
Networks 67 (4), 299-315, 2016
Mandate: US National Science Foundation
Solving a class of feature selection problems via fractional 0–1 programming
E Mehmanchi, A Gómez, OA Prokopyev
Annals of Operations Research 303 (1), 265-295, 2021
Mandate: US National Science Foundation
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