Ricardo Ñanculef

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 25

Top Topics

Machine Learning

Top Venues

Publications

Mauricio Solar, Victor Castañeda, Ricardo Ñanculef, Lioubov Dombrovskaia, Mauricio Araya
A Data Ingestion Procedure towards a Medical Images Repository. Sensors 24 (15) (2024)
Mario Mallea, Ricardo Ñanculef, Mauricio Araya
Enhancing Intra-modal Similarity in a Cross-Modal Triplet Loss. DS (2023)
Iván Pizarro, Ricardo Ñanculef, Carlos Valle
An Attention-Based Architecture for Hierarchical Classification With CNNs. IEEE Access 11 (2023)
Gonzalo Rivera Lazo, Hernán Astudillo, Ricardo Ñanculef
Attention Mechanisms in Process Mining: A Systematic Literature Review. CLEI (2023)
Manuel Alejandro Goyo, Ricardo Ñanculef
Cluster Distillation: Semi-supervised Time Series Classification through Clustering-based Self-supervision. SCCC (2022)
Gonzalo Rivera Lazo, Ricardo Ñanculef
Multi-attribute Transformers for Sequence Prediction in Business Process Management. DS (2022)
Francisco Andrades, Ricardo Ñanculef
A Method to Predict Semantic Relations on Artificial Intelligence Papers. CoRR (2022)
Ricardo Ñanculef, Francisco Alejandro Mena, Antonio Macaluso, Stefano Lodi, Claudio Sartori
Self-supervised Bernoulli Autoencoders for Semi-supervised Hashing. CIARP (2021)
Francisco Andrades, Ricardo Ñanculef
A Method to Predict Semantic Relations on Artificial Intelligence Papers. IEEE BigData (2021)
Ricardo Ñanculef, Francisco Alejandro Mena, Antonio Macaluso, Stefano Lodi, Claudio Sartori
Self-Supervised Bernoulli Autoencoders for Semi-Supervised Hashing. CoRR (2020)
Franklin Johnson, Alvaro Valderrama, Carlos Valle, Broderick Crawford, Ricardo Soto, Ricardo Ñanculef
Automating Configuration of Convolutional Neural Network Hyperparameters Using Genetic Algorithm. IEEE Access 8 (2020)
Rafik Mas'Ad, Ricardo Ñanculef, Hernán Astudillo
BlackSheep: Dynamic Effort Estimation in Agile Software Development using Machine Learning. CIbSE (2019)
Francisco Alejandro Mena, Ricardo Ñanculef
Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations. CIARP (2019)
Francisco Alejandro Mena, Ricardo Ñanculef
A Binary Variational Autoencoder for Hashing. CIARP (2019)
Francisco Alejandro Mena, Ricardo Ñanculef
Evaluating Bregman Divergences for Probability Learning from Crowd. CoRR (2019)
Carlos Valle, Ricardo Ñanculef, Héctor Allende, Claudio Moraga
LocalBoost: A Parallelizable Approach to Boosting Classifiers. Neural Process. Lett. 50 (1) (2019)
Cristian M. Orellana, Ricardo Ñanculef, Carlos Valle
Boosting Collaborative Filters for Drug-Target Interaction Prediction. CIARP (2018)
Simone Balocco, Mauricio González, Ricardo Ñanculef, Petia Radeva, Gabriel Thomas
Calcified Plaque Detection in IVUS Sequences: Preliminary Results Using Convolutional Nets. IWAIPR (2018)
Ricardo Ñanculef, Ilias N. Flaounas, Nello Cristianini
Efficient Classification of Multi-Labelled Text Streams by Clashing. CoRR (2016)
Emanuele Frandi, Ricardo Ñanculef, Stefano Lodi, Claudio Sartori, Johan A. K. Suykens
Fast and scalable Lasso via stochastic Frank-Wolfe methods with a convergence guarantee. Mach. Learn. 104 (2-3) (2016)
Julio Hurtado, Marcelo Mendoza, Ricardo Ñanculef
Boosting SpLSA for Text Classification. CIARP (2016)
Marcelo Aliquintuy, Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens
Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso. CIARP (2016)
Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens
A PARTAN-Accelerated Frank-Wolfe Algorithm for Large-Scale SVM Classification. CoRR (2015)
Emanuele Frandi, Ricardo Ñanculef, Stefano Lodi, Claudio Sartori, Johan A. K. Suykens
Fast and Scalable Lasso via Stochastic Frank-Wolfe Methods with a Convergence Guarantee. CoRR (2015)
Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens
A PARTAN-accelerated Frank-Wolfe algorithm for large-scale SVM classification. IJCNN (2015)
Emanuele Frandi, Ricardo Ñanculef, Johan A. K. Suykens
Complexity Issues and Randomization Strategies in Frank-Wolfe Algorithms for Machine Learning. CoRR (2014)
Ricardo Ñanculef, Ilias N. Flaounas, Nello Cristianini
Efficient classification of multi-labeled text streams by clashing. Expert Syst. Appl. 41 (11) (2014)
Ricardo Ñanculef, Emanuele Frandi, Claudio Sartori, Héctor Allende
A novel Frank-Wolfe algorithm. Analysis and applications to large-scale SVM training. Inf. Sci. 285 (2014)
Emanuele Frandi, Ricardo Ñanculef, Maria Grazia Gasparo, Stefano Lodi, Claudio Sartori
Training Support Vector Machines using Frank-Wolfe Optimization Methods. Int. J. Pattern Recognit. Artif. Intell. 27 (3) (2013)
Héctor Allende, Emanuele Frandi, Ricardo Ñanculef, Claudio Sartori
Novel Frank-Wolfe Methods for SVM Learning CoRR (2013)
Emanuele Frandi, Ricardo Ñanculef, Maria Grazia Gasparo, Stefano Lodi, Claudio Sartori
Training Support Vector Machines Using Frank-Wolfe Optimization Methods CoRR (2012)
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga
Training regression ensembles by sequential target correction and resampling. Inf. Sci. 195 (2012)
Ricardo Ñanculef, Erick López, Héctor Allende, Héctor Allende-Cid
An Ensemble Method for Incremental Classification in Stationary and Non-stationary Environments. CIARP (2011)
Ricardo Ñanculef, Héctor Allende, Stefano Lodi, Claudio Sartori
Two One-Pass Algorithms for Data Stream Classification Using Approximate MEBs. ICANNGA (2) (2011)
Stefano Lodi, Ricardo Ñanculef, Claudio Sartori
Single-Pass Distributed Learning of Multi-class SVMs Using Core-Sets. SDM (2010)
Emanuele Frandi, Maria Grazia Gasparo, Stefano Lodi, Ricardo Ñanculef, Claudio Sartori
A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls. CIARP (2010)
Diego Candel, Ricardo Ñanculef, Carlos Concha, Héctor Allende
A Sequential Minimal Optimization Algorithm for the All-Distances Support Vector Machine. CIARP (2010)
Stefano Lodi, Ricardo Ñanculef, Claudio Sartori
Learning Multi-Class Support Vector Models from Distributed Data using Core-Sets (Extended Abstract). SEBD (2010)
Stefano Lodi, Ricardo Ñanculef, Claudio Sartori
L2-SVM Training with Distributed Data. MATES (2009)
Ricardo Ñanculef, Carlos Concha, Héctor Allende, Diego Candel, Claudio Moraga
AD-SVMs: A light extension of SVMs for multicategory classification. Int. J. Hybrid Intell. Syst. 6 (2) (2009)
Ricardo Ñanculef, Carlos Concha, Héctor Allende, Diego Candel, Claudio Moraga
Multicategory SVMs by Minimizing the Distances among Convex-Hull Prototypes. HIS (2008)
Patricia Trejo, Ricardo Ñanculef, Héctor Allende, Claudio Moraga
Probabilistic Aggregation of Classifiers for Incremental Learning. IWANN (2007)
Héctor Allende-Cid, Rodrigo Salas, Héctor Allende, Ricardo Ñanculef
Robust Alternating AdaBoost. CIARP (2007)
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga
Bagging with Asymmetric Costs for Misclassified and Correctly Classified Examples. CIARP (2007)
Carlos Valle, Ricardo Ñanculef, Héctor Allende, Claudio Moraga
Two Bagging Algorithms with Coupled Learners to Encourage Diversity. IDA (2007)
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga
Ensemble Learning with Local Diversity. ICANN (1) (2006)
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga
Local Negative Correlation with Resampling. IDEAL (2006)
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga
Moderated Innovations in Self-poised Ensemble Learning. CIS (1) (2005)
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga
Self-poised Ensemble Learning. IDA (2005)
Ricardo Ñanculef, Carlos Concha, Claudio Moraga, Héctor Allende
Multiresolution Fuzzy Rule Systems. Fuzzy Days (2004)
Héctor Allende, Ricardo Ñanculef, Rodrigo Salas
Robust Bootstrapping Neural Networks. MICAI (2004)