Ricardo Ñanculef

According to our database, Ricardo Ñanculef authored at least 53 papers between 2004 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Data Ingestion Procedure towards a Medical Images Repository.

Mauricio Solar, Victor Castañeda, Ricardo Ñanculef, Lioubov Dombrovskaia, Mauricio Araya

Sensors, August, 2024

Hate Speech in Chilean Twitter.

Domingo Benoit, Ricardo Ñanculef

Dataset, July, 2024

InverseTime: A Self-Supervised Technique for Semi-Supervised Classification of Time Series.

Manuel Alejandro Goyo, Ricardo Ñanculef, Carlos Valle

IEEE Access, 2024

Adversarial Pairwise Multimodal Recommendation.

Mario Mallea, Ricardo Ñanculef, Denis Parra

Proceedings of the International Joint Conference on Neural Networks, 2024

Text-Based Feature-Free Automatic Algorithm Selection.

Amanda Salinas-Pinto, Bryan Alvarado-Ulloa, Dorit S. Hochbaum, Matías Francia-Carramiñana, Ricardo Ñanculef, Roberto Javier Asín Achá

Proceedings of the 16th International Joint Conference on Knowledge Discovery, 2024

ALPACS: Interoperable Repository of Medical Images.

Mauricio Solar, Mauricio Araya, Ricardo Ñanculef, Lioubov Dombrovskaia, Victor Castañeda, Ian Roberts

Proceedings of the L Latin American Computer Conference, 2024

Prediction of Peak-to-Peak Pressure Gradient in Patients with Aortic Coarctation Using Physics-Informed Neural Networks.

Sebastián Jara, Rodrigo Salas, Ricardo Ñanculef, Israel Valverde, Sergio Uribe, Julio Sotelo

Proceedings of the L Latin American Computer Conference, 2024

Recovering Latent Hierarchical Relationships in Image Datasets Through Hyperbolic Embeddings.

Ian Roberts, Mauricio Araya, Ricardo Ñanculef, Mario Mallea

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2024

2023

An Attention-Based Architecture for Hierarchical Classification With CNNs.

Iván Pizarro, Ricardo Ñanculef, Carlos Valle

IEEE Access, 2023

Enhancing Intra-modal Similarity in a Cross-Modal Triplet Loss.

Mario Mallea, Ricardo Ñanculef, Mauricio Araya

Proceedings of the Discovery Science - 26th International Conference, 2023

Attention Mechanisms in Process Mining: A Systematic Literature Review.

Gonzalo Rivera Lazo, Hernán Astudillo, Ricardo Ñanculef

Proceedings of the XLIX Latin American Computer Conference, 2023

2022

Cluster Distillation: Semi-supervised Time Series Classification through Clustering-based Self-supervision.

Manuel Alejandro Goyo, Ricardo Ñanculef

Proceedings of the 41st International Conference of the Chilean Computer Science Society, 2022

Multi-attribute Transformers for Sequence Prediction in Business Process Management.

Gonzalo Rivera Lazo, Ricardo Ñanculef

Proceedings of the Discovery Science - 25th International Conference, 2022

2021

Self-supervised Bernoulli Autoencoders for Semi-supervised Hashing.

Ricardo Ñanculef, Francisco Alejandro Mena, Antonio Macaluso, Stefano Lodi, Claudio Sartori

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2021

A Method to Predict Semantic Relations on Artificial Intelligence Papers.

Francisco Andrades, Ricardo Ñanculef

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Automating Configuration of Convolutional Neural Network Hyperparameters Using Genetic Algorithm.

Franklin Johnson, Alvaro Valderrama, Carlos Valle, Broderick Crawford, Ricardo Soto, Ricardo Ñanculef

IEEE Access, 2020

2019

LocalBoost: A Parallelizable Approach to Boosting Classifiers.

Carlos Valle, Ricardo Ñanculef, Héctor Allende, Claudio Moraga

Neural Process. Lett., 2019

Evaluating Bregman Divergences for Probability Learning from Crowd.

Francisco Alejandro Mena, Ricardo Ñanculef

CoRR, 2019

BlackSheep: Dynamic Effort Estimation in Agile Software Development using Machine Learning.

Rafik Mas'Ad, Ricardo Ñanculef, Hernán Astudillo

Proceedings of the XXII Iberoamerican Conference on Software Engineering, 2019

Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations.

Francisco Alejandro Mena, Ricardo Ñanculef

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2019

A Binary Variational Autoencoder for Hashing.

Francisco Alejandro Mena, Ricardo Ñanculef

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2019

2018

Calcified Plaque Detection in IVUS Sequences: Preliminary Results Using Convolutional Nets.

Simone Balocco, Mauricio González, Ricardo Ñanculef, Petia Radeva, Gabriel Thomas

Proceedings of the Progress in Artificial Intelligence and Pattern Recognition, 2018

Boosting Collaborative Filters for Drug-Target Interaction Prediction.

Cristian M. Orellana, Ricardo Ñanculef, Carlos Valle

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2018

2016

Fast and scalable Lasso via stochastic Frank-Wolfe methods with a convergence guarantee.

Emanuele Frandi, Ricardo Ñanculef, Stefano Lodi, Claudio Sartori, Johan A. K. Suykens

Mach. Learn., 2016

Efficient Classification of Multi-Labelled Text Streams by Clashing.

Ricardo Ñanculef, Ilias N. Flaounas, Nello Cristianini

CoRR, 2016

Boosting SpLSA for Text Classification.

Julio Hurtado, Marcelo Mendoza, Ricardo Ñanculef

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2016

Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso.

Marcelo Aliquintuy, Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2016

2015

A PARTAN-accelerated Frank-Wolfe algorithm for large-scale SVM classification.

Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

2014

A novel Frank-Wolfe algorithm. Analysis and applications to large-scale SVM training.

Ricardo Ñanculef, Emanuele Frandi, Claudio Sartori, Héctor Allende

Inf. Sci., 2014

Efficient classification of multi-labeled text streams by clashing.

Ricardo Ñanculef, Ilias N. Flaounas, Nello Cristianini

Expert Syst. Appl., 2014

Complexity Issues and Randomization Strategies in Frank-Wolfe Algorithms for Machine Learning.

Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens

CoRR, 2014

2013

Training Support Vector Machines using Frank-Wolfe Optimization Methods.

Emanuele Frandi, Ricardo Ñanculef, Maria Grazia Gasparo, Stefano Lodi, Claudio Sartori

Int. J. Pattern Recognit. Artif. Intell., 2013

Novel Frank-Wolfe Methods for SVM Learning

Héctor Allende, Emanuele Frandi, Ricardo Ñanculef, Claudio Sartori

CoRR, 2013

2012

Training regression ensembles by sequential target correction and resampling.

Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga

Inf. Sci., 2012

2011

Two One-Pass Algorithms for Data Stream Classification Using Approximate MEBs.

Ricardo Ñanculef, Héctor Allende, Stefano Lodi, Claudio Sartori

Proceedings of the Adaptive and Natural Computing Algorithms, 2011

An Ensemble Method for Incremental Classification in Stationary and Non-stationary Environments.

Ricardo Ñanculef, Erick López, Héctor Allende, Héctor Allende-Cid

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2011

2010

Learning Multi-Class Support Vector Models from Distributed Data using Core-Sets (Extended Abstract).

Stefano Lodi, Ricardo Ñanculef, Claudio Sartori

Proceedings of the Eighteenth Italian Symposium on Advanced Database Systems, 2010

Single-Pass Distributed Learning of Multi-class SVMs Using Core-Sets.

Stefano Lodi, Ricardo Ñanculef, Claudio Sartori

Proceedings of the SIAM International Conference on Data Mining, 2010

A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls.

Emanuele Frandi, Maria Grazia Gasparo, Stefano Lodi, Ricardo Ñanculef, Claudio Sartori

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2010

A Sequential Minimal Optimization Algorithm for the All-Distances Support Vector Machine.

Diego Candel, Ricardo Ñanculef, Carlos Concha, Héctor Allende

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2010

2009

AD-SVMs: A light extension of SVMs for multicategory classification.

Ricardo Ñanculef, Carlos Concha, Héctor Allende, Diego Candel, Claudio Moraga

Int. J. Hybrid Intell. Syst., 2009

L2-SVM Training with Distributed Data.

Stefano Lodi, Ricardo Ñanculef, Claudio Sartori

Proceedings of the Multiagent System Technologies, 7th German Conference, 2009

2008

Multicategory SVMs by Minimizing the Distances among Convex-Hull Prototypes.

Ricardo Ñanculef, Carlos Concha, Héctor Allende, Diego Candel, Claudio Moraga

Proceedings of the 8th International Conference on Hybrid Intelligent Systems (HIS 2008), 2008

2007

Probabilistic Aggregation of Classifiers for Incremental Learning.

Patricia Trejo, Ricardo Ñanculef, Héctor Allende, Claudio Moraga

Proceedings of the Computational and Ambient Intelligence, 2007

Two Bagging Algorithms with Coupled Learners to Encourage Diversity.

Carlos Valle, Ricardo Ñanculef, Héctor Allende, Claudio Moraga

Proceedings of the Advances in Intelligent Data Analysis VII, 2007

Bagging with Asymmetric Costs for Misclassified and Correctly Classified Examples.

Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga

Proceedings of the Progress in Pattern Recognition, 2007

Robust Alternating AdaBoost.

Héctor Allende-Cid, Rodrigo Salas, Héctor Allende, Ricardo Ñanculef

Proceedings of the Progress in Pattern Recognition, 2007

2006

Local Negative Correlation with Resampling.

Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga

Proceedings of the Intelligent Data Engineering and Automated Learning, 2006

Ensemble Learning with Local Diversity.

Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga

Proceedings of the Artificial Neural Networks, 2006

2005

Self-poised Ensemble Learning.

Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga

Proceedings of the Advances in Intelligent Data Analysis VI, 2005

Moderated Innovations in Self-poised Ensemble Learning.

Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga

Proceedings of the Computational Intelligence and Security, International Conference, 2005

2004

Robust Bootstrapping Neural Networks.

Héctor Allende, Ricardo Ñanculef, Rodrigo Salas

Proceedings of the MICAI 2004: Advances in Artificial Intelligence, 2004

Multiresolution Fuzzy Rule Systems.

Ricardo Ñanculef, Carlos Concha, Claudio Moraga, Héctor Allende

Proceedings of the Computational Intelligence, Theory and Applications, International Conference 8th Fuzzy Days, Dortmund, Germany, Sept. 29, 2004