1 citations · 1 across the 2 of their papers we have counts for
6 papers
Deep Reinforcement Learning for Routing a Heterogeneous Fleet of Vehicles
Jose Manuel Vera, Andres G. Abad
Motivated by the promising advances of deep-reinforcement learning (DRL) applied to cooperative multi-agent systems we propose a model and learning procedure to solve the Capacitat…
A fast multi-object tracking system using an object detector ensemble
Richard Cobos, Jefferson Hernandez, Andres G. Abad
Multiple-Object Tracking (MOT) is of crucial importance for applications such as retail video analytics and video surveillance. Object detectors are often the computational bottlen…
Learning from multivariate discrete sequential data using a restricted Boltzmann machine model
Jefferson Hernandez, Andres G. Abad
A restricted Boltzmann machine (RBM) is a generative neural-network model with many novel applications such as collaborative filtering and acoustic modeling. An RBM lacks the capac…
Collaborative Filtering using Denoising Auto-Encoders for Market Basket Data
Andres G. Abad, Luis I. Reyes-Castro
Recommender systems (RS) help users navigate large sets of items in the search for "interesting" ones. One approach to RS is Collaborative Filtering (CF), which is based on the ide…
A Probabilistic Adaptive Search System for Exploring the Face Space
Andres G. Abad, Luis I. Reyes Castro
Face recall is a basic human cognitive process performed routinely, e.g., when meeting someone and determining if we have met that person before. Assisting a subject during face re…
A Dynamic Bayesian Network Model for Inventory Level Estimation in Retail Marketing
Luis I. Reyes-Castro, Andres G. Abad
Many retailers today employ inventory management systems based on Re-Order Point Policies, most of which rely on the assumption that all decreases in product inventory levels resul…