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pro vyhledávání: '"ELIAS, B"'
We present $\textit{Learn2Aggregate}$, a machine learning (ML) framework for optimizing the generation of Chv\'atal-Gomory (CG) cuts in mixed integer linear programming (MILP). The framework trains a graph neural network to classify useful constraint
Externí odkaz:
http://arxiv.org/abs/2409.06559
Mixed-Integer Rounding (MIR) cuts are effective at improving the dual bound in Mixed-Integer Linear Programming (MIP). However, in practice, MIR cuts are separated heuristically rather than using optimization as the latter is prohibitively expensive.
Externí odkaz:
http://arxiv.org/abs/2408.08449
In multicriteria decision-making, a user seeks a set of non-dominated solutions to a (constrained) multiobjective optimization problem, the so-called Pareto frontier. In this work, we seek to bring a state-of-the-art method for exact multiobjective i
Externí odkaz:
http://arxiv.org/abs/2403.02482
Bilevel optimization deals with nested problems in which a leader takes the first decision to minimize their objective function while accounting for a follower's best-response reaction. Constrained bilevel problems with integer variables are particul
Externí odkaz:
http://arxiv.org/abs/2402.02552
Autor:
Krestenitis, Marios, Raptis, Emmanuel K., Kapoutsis, Athanasios Ch., Ioannidis, Konstantinos, Kosmatopoulos, Elias B., Vrochidis, Stefanos
Publikováno v:
Robotics and Autonomous Systems (2023): 104581
This paper deals with the problem of informative path planning for a UAV deployed for precision agriculture applications. First, we observe that the ``fear of missing out'' data lead to uniform, conservative scanning policies over the whole agricultu
Externí odkaz:
http://arxiv.org/abs/2312.09730
Autor:
Tang, Bo, Khalil, Elias B.
The end-to-end predict-then-optimize framework, also known as decision-focused learning, has gained popularity for its ability to integrate optimization into the training procedure of machine learning models that predict the unknown cost (objective f
Externí odkaz:
http://arxiv.org/abs/2312.07718
Autor:
Toosi, Tahereh, Issa, Elias B.
In natural vision, feedback connections support versatile visual inference capabilities such as making sense of the occluded or noisy bottom-up sensory information or mediating pure top-down processes such as imagination. However, the mechanisms by w
Externí odkaz:
http://arxiv.org/abs/2310.20599
Robust optimization provides a mathematical framework for modeling and solving decision-making problems under worst-case uncertainty. This work addresses two-stage robust optimization (2RO) problems (also called adjustable robust optimization), where
Externí odkaz:
http://arxiv.org/abs/2310.04345
Autor:
Toosi, Tahereh, Issa, Elias B.
Publikováno v:
International Conference on Learning Representations (ICLR), 2023
Representational straightening refers to a decrease in curvature of visual feature representations of a sequence of frames taken from natural movies. Prior work established straightening in neural representations of the primate primary visual cortex
Externí odkaz:
http://arxiv.org/abs/2308.13870