Search Results for author: Pablo Moscato

Found 8 papers, 2 papers with code

A Memetic Algorithm To Find a Hamiltonian Cycle in a Hamiltonian Graph

no code implementations1 Feb 2024 Sarwan Ali, Pablo Moscato

We present a memetic algorithm (\maa) approach for finding a Hamiltonian cycle in a Hamiltonian graph.

Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays

no code implementations13 Apr 2021 Pablo Moscato, Hugh Craig, Gabriel Egan, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira

In this study, we took a set of Shakespeare-era plays (181 plays from the period 1585--1610), added the best-guess dates for them from a standard reference work as metadata, and calculated a set of probabilities of individual words in these samples.

regression

Learning to extrapolate using continued fractions: Predicting the critical temperature of superconductor materials

no code implementations27 Nov 2020 Pablo Moscato, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon C. de Oliveira

We refer to $S$ as the training set and aim to identify a low-complexity mathematical model that can effectively approximate this target function for new instances $\mathbf{x}$.

regression

Analytic Continued Fractions for Regression: A Memetic Algorithm Approach

no code implementations18 Dec 2019 Pablo Moscato, Haoyuan Sun, Mohammad Nazmul Haque

We present an approach for regression problems that employs analytic continued fractions as a novel representation.

BIG-bench Machine Learning regression +1

mQAPViz: A divide-and-conquer multi-objective optimization algorithm to compute large data visualizations

no code implementations2 Apr 2018 Claudio Sanhueza, Francia Jiménez, Regina Berretta, Pablo Moscato

We propose mQAPViz, a divide-and-conquer multi-objective optimization algorithm to compute large-scale data visualizations.

PasMoQAP: A Parallel Asynchronous Memetic Algorithm for solving the Multi-Objective Quadratic Assignment Problem

1 code implementation27 Jun 2017 Claudio Sanhueza, Francia Jimenez, Regina Berretta, Pablo Moscato

Multi-Objective Evolutionary Algorithms (MOEAs) have been extensively used to address MOPs because are able to approximate a set of non-dominated high-quality solutions.

Evolutionary Algorithms

Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks

1 code implementation15 Jun 2017 Shannon Fenn, Pablo Moscato

This improvement increases as the loss places more emphasis on target order and is strongly correlated with an easy-to-hard curricula.

Multi-Label Classification

Separating Sets of Strings by Finding Matching Patterns is Almost Always Hard

no code implementations12 Apr 2016 Giuseppe Lancia, Luke Mathieson, Pablo Moscato

We study the complexity of the problem of searching for a set of patterns that separate two given sets of strings.

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