2 code implementations • 8 Apr 2024 • Yigeng Zhang, Fabio A. González, Thamar Solorio
Reading comprehension continues to be a crucial research focus in the NLP community.
1 code implementation • 18 Sep 2023 • Yigeng Zhang, Mahsa Shafaei, Fabio A. González, Thamar Solorio
In this work, we introduce a pioneering research challenge: evaluating positive and potentially harmful messages within music products.
1 code implementation • 21 Jun 2023 • Raúl Ramos-Pollán, Fabio A. González
This work addresses the challenge of training supervised machine or deep learning models on orbiting platforms where we are generally constrained by limited on-board hardware capabilities and restricted uplink bandwidths to upload.
2 code implementations • 26 May 2023 • Fabio A. González, Raúl Ramos-Pollán, Joseph A. Gallego-Mejia
In doing so, we provide a versatile representation of marginal and joint probability distributions that allows us to develop a differentiable, compositional, and reversible inference procedure that covers a wide range of machine learning tasks, including density estimation, discriminative learning, and generative modeling.
no code implementations • 25 Jan 2023 • Anamaria Mojica-Hanke, Andrea Bayona, Mario Linares-Vásquez, Steffen Herbold, Fabio A. González
In particular, Software Engineering (SE) is one of those disciplines in which ML has been used for multiple tasks, like software categorization, bugs prediction, and testing.
1 code implementation • 15 Nov 2022 • Joseph Gallego-Mejia, Oscar Bustos-Brinez, Fabio A. González
This paper presents an anomaly detection model that combines the strong statistical foundation of density-estimation-based anomaly detection methods with the representation-learning ability of deep-learning models.
1 code implementation • 26 Oct 2022 • Oscar Bustos-Brinez, Joseph Gallego-Mejia, Fabio A. González
The prediction phase complexity of the proposed algorithm is constant relative to the training data size, and it performs well in data sets with different anomaly rates.
no code implementations • 4 Aug 2022 • Jose Miguel Arrieta Ramos, Oscar Perdómo, Fabio A. González
This paper presents a semi-supervised method that leverages unlabeled images and labeled ones to train a model that detects diabetic retinopathy.
1 code implementation • 2 Aug 2022 • Joseph A. Gallego, Juan F. Osorio, Fabio A. González
In this paper, we systematically evaluate the novel DMKDE algorithm and compare it with other state-of-the-art fast procedures for approximating the kernel density estimation method on different synthetic data sets.
1 code implementation • 1 Aug 2022 • Joseph A. Gallego, Fabio A. González
Density estimation is a fundamental task in statistics and machine learning applications.
no code implementations • 18 Jun 2022 • Vladimir Vargas-Calderón, Herbert Vinck-Posada, Fabio A. González
We consider the Feynman-Kitaev formalism applied to a spin chain described by the transverse field Ising model.
no code implementations • 28 Mar 2022 • Vladimir Vargas-Calderón, Fabio A. González, Herbert Vinck-Posada
We demonstrate the implementation of a novel machine learning framework for probability density estimation and classification using quantum circuits.
no code implementations • 14 Oct 2021 • Melissa delaPava, Hernán Ríos, Francisco J. Rodríguez, Oscar J. Perdomo, Fabio A. González
The kaggle EyePACS subset is used as a training set and the Messidor-2 as a test set for lesions and DR classification models.
no code implementations • 20 Jul 2021 • Diego H. Useche, Andres Giraldo-Carvajal, Hernan M. Zuluaga-Bucheli, Jose A. Jaramillo-Villegas, Fabio A. González
Results show that the proposed method is a viable strategy to implement supervised classification and density estimation in a high-dimensional quantum computer.
no code implementations • 4 Mar 2021 • Santiago Toledo-Cortés, Diego H. Useche, Fabio A. González
Prostate cancer (PCa) is one of the most common and aggressive cancers worldwide.
1 code implementation • 8 Feb 2021 • Fabio A. González, Alejandro Gallego, Santiago Toledo-Cortés, Vladimir Vargas-Calderón
It is a powerful formalism to represent both the quantum and classical uncertainty of quantum systems and to express different statistical operations such as measurement, system combination and expectations as linear algebra operations.
2 code implementations • 29 Jul 2020 • Santiago Toledo-Cortés, Melissa De La Pava, Oscar Perdómo, Fabio A. González
In this paper, a hybrid Deep Learning-Gaussian process method for DR diagnosis and uncertainty quantification is presented.
2 code implementations • 15 Jun 2020 • Juan S. Lara, Fabio A. González
The dissimilarity mixture autoencoder (DMAE) is a neural network model for feature-based clustering that incorporates a flexible dissimilarity function and can be integrated into any kind of deep learning architecture.
2 code implementations • 2 Apr 2020 • Fabio A. González, Vladimir Vargas-Calderón, Herbert Vinck-Posada
Prediction of the label for a new sample is made by performing a projective measurement on the bipartite system with an operator, prepared from the new input sample, and applying a partial trace to obtain the state of the subsystem representing the output.
no code implementations • NAACL 2018 • Gustavo Aguilar, A. Pastor López-Monroy, Fabio A. González, Thamar Solorio
Our systems outperform the current F1 scores of the state of the art on the Workshop on Noisy User-generated Text 2017 dataset by 2. 45% and 3. 69%, establishing a more suitable approach for social media environments.
Ranked #17 on Named Entity Recognition (NER) on WNUT 2017
no code implementations • 7 Mar 2019 • Fabio A. González, Juan C. Caicedo
LTA is a valuable technique for document analysis and representation, which has been extensively used in information retrieval and machine learning.
9 code implementations • 7 Feb 2017 • John Arevalo, Thamar Solorio, Manuel Montes-y-Gómez, Fabio A. González
The Gated Multimodal Unit (GMU) model is intended to be used as an internal unit in a neural network architecture whose purpose is to find an intermediate representation based on a combination of data from different modalities.