Zobrazeno 1 - 10
of 743
pro vyhledávání: '"Muñoz, Gonzalo"'
Autor:
Carrasco, Pablo, Muñoz, Gonzalo
The non-convex nature of trained neural networks has created significant obstacles in their incorporation into optimization models. Considering the wide array of applications that this embedding has, the optimization and deep learning communities hav
Externí odkaz:
http://arxiv.org/abs/2410.23362
Dealing with uncertainty in optimization parameters is an important and longstanding challenge. Typically, uncertain parameters are predicted accurately, and then a deterministic optimization problem is solved. However, the decisions produced by this
Externí odkaz:
http://arxiv.org/abs/2312.17640
The use of Mixed-Integer Linear Programming (MILP) models to represent neural networks with Rectified Linear Unit (ReLU) activations has become increasingly widespread in the last decade. This has enabled the use of MILP technology to test-or stress-
Externí odkaz:
http://arxiv.org/abs/2312.16699
In the past decade, deep learning became the prevalent methodology for predictive modeling thanks to the remarkable accuracy of deep neural networks in tasks such as computer vision and natural language processing. Meanwhile, the structure of neural
Externí odkaz:
http://arxiv.org/abs/2305.00241
Deep learning has revolutionized the computer vision and image classification domains. In this context Convolutional Neural Networks (CNNs) based architectures are the most widely applied models. In this article, we introduced two procedures for trai
Externí odkaz:
http://arxiv.org/abs/2302.11327
This paper presents a computationally efficient variant of gradient boosting for multi-class classification and multi-output regression tasks. Standard gradient boosting uses a 1-vs-all strategy for classifications tasks with more than two classes. T
Externí odkaz:
http://arxiv.org/abs/2211.14599
The intersection cut framework was introduced by Balas in 1971 as a method for generating cutting planes in integer optimization. In this framework, one uses a full-dimensional convex $S$-free set, where $S$ is the feasible region of the integer prog
Externí odkaz:
http://arxiv.org/abs/2211.05185
A branch-and-bound (BB) tree certifies a dual bound on the value of an integer program. In this work, we introduce the tree compression problem (TCP): Given a BB tree T that certifies a dual bound, can we obtain a smaller tree with the same (or stron
Externí odkaz:
http://arxiv.org/abs/2211.02727
We study linear bilevel programming problems whose lower-level objective is given by a random cost vector with known distribution. We consider the case where this distribution is nonatomic, allowing to reformulate the problem of the leader using the
Externí odkaz:
http://arxiv.org/abs/2211.02268
Autor:
de Andres, Daniel, Yepes, Gustavo, Sembolini, Federico, Martínez-Muñoz, Gonzalo, Cui, Weiguang, Robledo, Francisco, Chuang, Chia-Hsun, Rasia, Elena
In this paper we study the applicability of a set of supervised machine learning (ML) models specifically trained to infer observed related properties of the baryonic component (stars and gas) from a set of features of dark matter only cluster-size h
Externí odkaz:
http://arxiv.org/abs/2204.10751