Ricardo Ñanculef

发表

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

Claudio Sartori, Stefano Lodi, Ricardo Ñanculef, 2010, SEBD.

Self-poised Ensemble Learning

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2005, IDA.

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

Claudio Sartori, Stefano Lodi, Ricardo Ñanculef, 2010, SDM.

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

Johan A. K. Suykens, Claudio Sartori, Stefano Lodi, 2015, Machine Learning.

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

Claudio Sartori, Héctor Allende, Ricardo Ñanculef, 2013, Inf. Sci..

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

Petia Radeva, Gabriel Thomas, Ricardo Ñanculef, 2018, IWAIPR.

Robust Alternating AdaBoost

Rodrigo Salas, Héctor Allende, Ricardo Ñanculef, 2007, CIARP.

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

Johan A. K. Suykens, Ricardo Ñanculef, Emanuele Frandi, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Boosting SpLSA for Text Classification

Ricardo Ñanculef, Marcelo Mendoza, Julio Hurtado, 2016, CIARP.

Multicategory SVMs by Minimizing the Distances among Convex-Hull Prototypes

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

Collective annotation patterns in learning from crowds

Ricardo Ñanculef, Carlos Valle, Francisco Alejandro Mena, 2020 .

Training Support Vector Machines using Frank-Wolfe Optimization Methods pdf

Claudio Sartori, Stefano Lodi, Ricardo Ñanculef, 2012, Int. J. Pattern Recognit. Artif. Intell..

Training regression ensembles by sequential target correction and resampling

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2012, Inf. Sci..

Interpretable and effective hashing via Bernoulli variational auto-encoders

Ricardo Ñanculef, Carlos Valle, Francisco Alejandro Mena, 2020 .

LocalBoost: A Parallelizable Approach to Boosting Classifiers

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2018, Neural Processing Letters.

Multiresolution Fuzzy Rule Systems

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2004, Fuzzy Days.

Novel Frank-Wolfe Methods for SVM Learning pdf

Claudio Sartori, Héctor Allende, Ricardo Ñanculef, 2013, ArXiv.

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

Hernán Astudillo, Ricardo Ñanculef, Rafik Mas'Ad, 2019, CIbSE.

A New Algorithm for Training SVMs Using Approximate Minimal Enclosing Balls

Claudio Sartori, Stefano Lodi, Ricardo Ñanculef, 2010, CIARP.

L2-SVM Training with Distributed Data

Claudio Sartori, Stefano Lodi, Ricardo Ñanculef, 2009, MATES.

Moderated Innovations in Self-poised Ensemble Learning

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2005, CIS.

A Binary Variational Autoencoder for Hashing

Ricardo Ñanculef, Francisco A. Mena, 2019, CIARP.

Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations

Ricardo Ñanculef, Francisco A. Mena, 2019, CIARP.

Automating Configuration of Convolutional Neural Network Hyperparameters Using Genetic Algorithm

Broderick Crawford, Ricardo Soto, Franklin Johnson, 2020, IEEE Access.

Training Convolutional Nets to Detect Calcified Plaque in IVUS Sequences

Petia Radeva, Ricardo Ñanculef, Simone Balocco, 2020 .

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

Héctor Allende, Ricardo Ñanculef, Carlos Concha, 2010, CIARP.

Evaluating Bregman Divergences for Probability Learning from Crowd pdf

Ricardo Ñanculef, Francisco A. Mena, Ricardo Ñanculef, 2019, ArXiv.

Bagging with Asymmetric Costs for Misclassified and Correctly Classified Examples

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2007, CIARP.

Boosting Collaborative Filters for Drug-Target Interaction Prediction

Ricardo Ñanculef, Carlos Valle, Cristian M. Orellana, 2018, CIARP.

Ensemble Learning with Local Diversity

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2006, ICANN.

Efficient classification of multi-labeled text streams by clashing pdf

Nello Cristianini, Ricardo Ñanculef, Ilias N. Flaounas, 2014, Expert Syst. Appl..

Two Bagging Algorithms with Coupled Learners to Encourage Diversity

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2007, IDA.

Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso

Johan A. K. Suykens, Ricardo Ñanculef, Emanuele Frandi, 2016, CIARP.

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

Héctor Allende, Ricardo Ñanculef, Héctor Allende-Cid, 2011, CIARP.

Robust Bootstrapping Neural Networks

Rodrigo Salas, Héctor Allende, Ricardo Ñanculef, 2004, MICAI.

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

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2009, Int. J. Hybrid Intell. Syst..

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

Johan A. K. Suykens, Ricardo Ñanculef, Emanuele Frandi, 2014, NIPS 2014.

Probabilistic Aggregation of Classifiers for Incremental Learning

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2007, IWANN.

Local Negative Correlation with Resampling

Claudio Moraga, Héctor Allende, Ricardo Ñanculef, 2006, IDEAL.

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

Claudio Sartori, Héctor Allende, Stefano Lodi, 2011, ICANNGA.

A Method to Predict Semantic Relations on Artificial Intelligence Papers

Ricardo Ñanculef, Francisco Andrades, 2021, 2021 IEEE International Conference on Big Data (Big Data).