Andres Mendez-Vazquez

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Andres Mendez-Vazquez has participated in several projects for the USA Army, Mexican Air Force, Oracle MDC, IBM Mexico, and several startups. As a professional of Machine Learning and Artificial Intelligence, his main task is to propose, design, develop and program algorithms for specific solutions on those areas. Additionally, he is an associate research professor at Cinvestav Guadalajara where he leads a Machine Learning Research Group. He got his PhD in Computer Engineering doing Machine Learning at the University of Florida, USA . His research and interests are in applying, designing and developing Machine Learning, Deep Learning and Computational Mathematics algorithms.

machine learning analysis of algorithms data structures artificial intelligence linear algebra algorithms neural networks complexity deep learning bayesian networks probability map bayesian estimation automatic differentiation backpropagation company profiles reinforcement learning deep heuristic search tensors data sciences unsupervised learning clustering k-means learning boosting statistical learning risk functional loss functions function approximation feature selection convex optimization data analytics semi-supervised unsupurvised supervised data mining logistic regression markov chains monte carlo math for intelligent systems b-trees divide and conquer skip list genetic algorithms schema theorem amortized analysis binary trees hash tables search median statistics linear sorting sorting dual problem lagrangian's

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Andres Mendez-Vazquez

Cache aware hybrid sorter

omp-and-k-svd - Gdc2013

Mevia Introduction in Tegucigalpa, Honduras - Honduras Global

Non-exhaustive, Overlapping K-means

EGLA Licensing and Stadson Technologies

Matrix methods for Hadoop

Edwin Hernandez Presentation for Local Computer Networks n 2004