Pablo M. Granitto

Publication Activity (10 Years)

Years Active: 2000-2021
Publications (10 Years): 15

Top Topics

Feature Selection

Cdna Microarray

Top Venues

Expert Syst. Appl.

Astron. Comput.

Comput. Electron. Agric.

Publications

Juan B. Cabral, Marcelo Lares, Sebastián Gurovich, D. Minniti, Pablo M. Granitto
Drifting Features: Detection and evaluation in the context of automatic RRLs identification in VVV. CoRR (2021)
Juan B. Cabral, Felipe Ramos, Sebastián Gurovich, Pablo M. Granitto
Automatic Catalog of RRLyrae from ~ 14 million VVV Light Curves: How far can we go with traditional machine-learning? CoRR (2020)
Lucas C. Uzal, Guillermo L. Grinblat, Rafael Namías, Mónica G. Larese, Stefano Bianchi, E. N. Morandi, Pablo M. Granitto
Seed-per-pod estimation for plant breeding using deep learning. Comput. Electron. Agric. 150 (2018)
Juan B. Cabral, Bruno Sánchez, Felipe Ramos, Sebastián Gurovich, Pablo M. Granitto, Jacob VanderPlas
From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning. Astron. Comput. 25 (2018)
Guillermo Leale, Ariel E. Bayá, Diego H. Milone, Pablo M. Granitto, Georgina Stegmayer
Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 15 (1) (2018)
Juan B. Cabral, Bruno Sánchez, Felipe Ramos, Sebastián Gurovich, Pablo M. Granitto, Jacob VanderPlas
From FATS to feets: Further improvements to an astronomical feature extraction tool based on machine learning. CoRR (2018)
Juan B. Cabral, Bruno Sánchez, Martin Beroiz, Mariano Domínguez, Marcelo Lares, Sebastián Gurovich, Pablo M. Granitto
Corral framework: Trustworthy and fully functional data intensive parallel astronomical pipelines. Astron. Comput. 20 (2017)
Juan B. Cabral, Bruno Sánchez, Martin Beroiz, Mariano Domínguez, Marcelo Lares, Sebastián Gurovich, Pablo M. Granitto
Corral Framework: Trustworthy and Fully Functional Data Intensive Parallel Astronomical Pipelines. CoRR (2017)
Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto
Class-Splitting Generative Adversarial Networks. CoRR (2017)
Javier Izetta, Pablo F. Verdes, Pablo M. Granitto
Improved multiclass feature selection via list combination. Expert Syst. Appl. 88 (2017)
Guillermo L. Grinblat, Ariel E. Bayá, Diego H. Milone, Pablo M. Granitto, Georgina Stegmayer
Inferring unknown biological function by integration of GO annotations and gene expression data. CoRR (2016)
Guillermo L. Grinblat, Lucas C. Uzal, Mónica G. Larese, Pablo M. Granitto
Deep learning for plant identification using vein morphological patterns. Comput. Electron. Agric. 127 (2016)
Mónica G. Larese, Pablo M. Granitto
Finding local leaf vein patterns for legume characterization and classification. Mach. Vis. Appl. 27 (5) (2016)
Ariel E. Bayá, Mónica G. Larese, Pablo M. Granitto
Clustering using PK-D: A connectivity and density dissimilarity. Expert Syst. Appl. 51 (2016)
Guillermo L. Grinblat, Lucas C. Uzal, Pablo F. Verdes, Pablo M. Granitto
Nonstationary regression with support vector machines. Neural Comput. Appl. 26 (3) (2015)
Mónica G. Larese, Rafael Namías, Roque M. Craviotto, Miriam R. Arango, Carina Gallo, Pablo M. Granitto
Automatic classification of legumes using leaf vein image features. Pattern Recognit. 47 (1) (2014)
Mónica G. Larese, Pablo M. Granitto
Hybrid Consensus Learning for Legume Species and Cultivars Classification. ECCV Workshops (4) (2014)
Mónica G. Larese, Ariel E. Bayá, Roque M. Craviotto, Miriam R. Arango, Carina Gallo, Pablo M. Granitto
Multiscale recognition of legume varieties based on leaf venation images. Expert Syst. Appl. 41 (10) (2014)
Ariel E. Bayá, Pablo M. Granitto
How Many Clusters: A Validation Index for Arbitrary-Shaped Clusters. IEEE ACM Trans. Comput. Biol. Bioinform. 10 (2) (2013)
Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto
Abrupt change detection with One-Class Time-Adaptive Support Vector Machines. Expert Syst. Appl. 40 (18) (2013)
Mónica G. Larese, Pablo M. Granitto, Juan C. Gómez
Spot defects detection in cDNA microarray images. Pattern Anal. Appl. 16 (3) (2013)
Hernán Ahumada, Pablo M. Granitto
A Simple Hybrid Method for Semi-Supervised Learning. CIARP (2012)
Mónica G. Larese, Roque M. Craviotto, Miriam R. Arango, Carina Gallo, Pablo M. Granitto
Legume Identification by Leaf Vein Images Classification. CIARP (2012)
Guillermo L. Grinblat, Lucas C. Uzal, H. Alejandro Ceccatto, Pablo M. Granitto
Solving Nonstationary Classification Problems With Coupled Support Vector Machines. IEEE Trans. Neural Networks 22 (1) (2011)
Hernán Ahumada, Guillermo L. Grinblat, Pablo M. Granitto
Unsupervized Data-Driven Partitioning of Multiclass Problems. ICANN (1) (2011)
Ariel E. Bayá, Pablo M. Granitto
Improved Gene Expression Clustering with the Parameter-Free PKNNG Metric. BSB (2011)
Hernán Ahumada, Guillermo L. Grinblat, Lucas C. Uzal, H. Alejandro Ceccatto, Pablo M. Granitto
Evaluation of a new hybrid algorithm for highly imbalanced classification problems. Int. J. Hybrid Intell. Syst. 8 (4) (2011)
Ariel E. Bayá, Pablo M. Granitto
Clustering gene expression data with a penalized graph-based metric. BMC Bioinform. 12 (2011)
Ariel E. Bayá, Pablo M. Granitto
Improved Graph-Based Metrics for Clustering High-Dimensional Datasets. IBERAMIA (2010)
Mónica G. Larese, Pablo M. Granitto, Juan C. Gómez
Learning to Discover Faulty Spots in cDNA Microarrays. IBERAMIA (2010)
Guillermo L. Grinblat, Javier Izetta, Pablo M. Granitto
SVM Based Feature Selection: Why Are We Using the Dual? IBERAMIA (2010)
Ariel E. Bayá, Pablo M. Granitto
Penalized K-Nearest-Neighbor-Graph Based Metrics for Clustering CoRR (2010)
Pablo M. Granitto, Andrés Burgos
Feature selection on wide multiclass problems using OVA-RFE. Inteligencia Artif. 13 (44) (2009)
Guillermo L. Grinblat, Pablo M. Granitto, H. Alejandro Ceccatto
Time-Adaptive Support Vector Machines. Inteligencia Artif. 12 (40) (2008)
Hernán Ahumada, Guillermo L. Grinblat, Lucas C. Uzal, Pablo M. Granitto, H. Alejandro Ceccatto
REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems. HIS (2008)
Pablo M. Granitto, Franco Biasioli, Cesare Furlanello, Flavia Gasperi
Efficient Feature Selection for PTR-MS Fingerprinting of Agroindustrial Products. ICANN (2) (2008)
Ariel E. Bayá, Pablo M. Granitto
ISOMAP based metrics for clustering. Inteligencia Artif. 12 (37) (2008)
Ariel E. Bayá, Mónica G. Larese, Pablo M. Granitto, Juan Carlos Gomez, Elizabeth Tapia
Gene Set Enrichment Analysis Using Non-parametric Scores. BSB (2007)
Pablo F. Verdes, Pablo M. Granitto, María I. Széliga, A. Rébola, H. Alejandro Ceccatto
Symmetric-embedding prediction of the CATS benchmark. Neurocomputing 70 (13-15) (2007)
Pablo M. Granitto, Pablo F. Verdes, H. Alejandro Ceccatto
Neural network ensembles: Evaluation of aggregation algorithms CoRR (2005)
Pablo M. Granitto, Pablo F. Verdes, H. Alejandro Ceccatto
Neural network ensembles: evaluation of aggregation algorithms. Artif. Intell. 163 (2) (2005)
María I. Széliga, Pablo F. Verdes, Pablo M. Granitto, H. Alejandro Ceccatto
Artificial Neural Network Learning of Nonstationary Behavior in Time Series. Int. J. Neural Syst. 13 (2) (2003)
María I. Széliga, Pablo F. Verdes, Pablo M. Granitto, H. Alejandro Ceccatto
Extracting Driving Signals from Non-Stationary Time Series. SBRN (2002)
Pablo M. Granitto, Pablo F. Verdes, Hugo D. Navone, H. Alejandro Ceccatto
Aggregation Algorithms for Neural Network Ensemble Construction . SBRN (2002)
Pablo M. Granitto, Pablo F. Verdes, Hugo D. Navone, H. Alejandro Ceccatto
A Late-Stopping Method for Optimal Aggregation of Neural Networks. Int. J. Neural Syst. 11 (3) (2001)
Hugo D. Navone, Pablo M. Granitto, Pablo F. Verdes, H. Alejandro Ceccatto
A Learning Algorithm For Neural Network Ensembles. Inteligencia Artif. 5 (12) (2001)
Hugo D. Navone, Pablo F. Verdes, Pablo M. Granitto, H. Alejandro Ceccatto
Selecting Diverse Members of Neural Network Ensembles. SBRN (2000)