Fully Distributed Bayesian Optimization with Stochastic Policies

Bayesian optimization has become a popular method for high-throughput computing, like the design of computer experiments or hyperparameter tuning of expensive models, where sample efficiency is mandatory. In these applications, distributed and scalable architectures are a necessity. However, Bayesian optimization is mostly sequential. Even parallel variants require certain computations between samples, limiting the parallelization bandwidth. Thompson sampling has been previously applied for distributed Bayesian optimization. But, when compared with other acquisition functions in the sequential setting, Thompson sampling is known to perform suboptimally. In this paper, we present a new method for fully distributed Bayesian optimization, which can be combined with any acquisition function. Our approach considers Bayesian optimization as a partially observable Markov decision process. In this context, stochastic policies, such as the Boltzmann policy, have some interesting properties which can also be studied for Bayesian optimization. Furthermore, the Boltzmann policy trivially allows a distributed Bayesian optimization implementation with high level of parallelism and scalability. We present results in several benchmarks and applications that shows the performance of our method

Analysis of a low-cost open robot for machine learning teaching

[Resumen] En este trabajo estudiamos el comportamiento, ventajas e inconvenientes del robot Trifinger para la docencia de estudiantes de ingeniería y automática. El robot Trifinger es un robot de diseño abierto a nivel hardware con piezas realizadas con impresión 3D y componentes (electrónica, motores...) estándar y disponibles comercialmente. El software también es abierto e incorpora un simulador realizado en Pybullet que simplifica el prototipado de soluciones y puede usarse como una primera aproximación de los estudiantes. En concreto, en este trabajo evaluamos su potencial uso para la docencia de aprendizaje automático en general y de aprendizaje por refuerzo en particular, una línea que esta permeando todas las áreas de conocimiento y tiene gran potencial en el mundo de la automática. Evaluamos el comportamiento de varios algoritmos que están en el estado del arte del aprendizaje por refuerzo en varias tareas planteadas con el uso robot, demostrando que la plataforma es a la vez una herramienta sencilla de usar y manejar, pero a la vez desafiante y compleja incluso para el estado del arte.[Abstract] In this work we study the behavior, advantages and disadvantages of the Trifinger robot for teaching engineering and automation students. The Trifinger robot is an open design robot at hardware level with parts made with 3D printing and off-the-shelf components (electronics, motors...). The software is also open and incorporates a simulator made in Pybullet that simplifies the prototyping of solutions and can be used as a first approach for students. Specifically, in this work we evaluate its potential use for teaching machine learning in general and reinforcement learning in particular, a line that is permeating all areas of knowledge and has great potential in the world of automation. We evaluate the behavior of several algorithms that are in the state of the art of reinforcement learning in several tasks posed with the use of robots, demonstrating that the platform is both a simple tool to use and manage, but at the same time challenging and complex even for the state of the art.Ministerio de Ciencia e Innovación; PID2021-125209OB-I00Ministerio de Ciencia e Innovación; TED2021-131150B-I0

ALIFE: Caracterización Térmica De La Fermentación Del Café

La fermentación del café es una de las operaciones críticas en el proceso de beneficiado por su impacto en la calidad organoléptica del producto final. De forma general la mayor parte de las explotaciones carecen de tecnificación alguna del fermentador, no teniendo el operario ninguna información objetiva sobre la evolución de los parámetros físico-químicos de control del proceso que le ayuden a la toma de decisión. El objetivo de este trabajo es la integración multi-distribuida de sensores de bajo coste y alta fiabilidad para supervisión de la operación de fermentación del café en origen. Concretamente se ha centrado en la caracterización térmica del proceso de fermentación, mediante la instalación multidistribuida de sensores inalámbricos de temperatura (TurboTag ®) en fermentadores de café en Colombia. El análisis: temporal de la evolución de la temperatura a lo largo del proceso de fermentación y complejo mediante diagrama de fases o de cinética de la evolución de las temperaturas, permiten en este trabajo caracterizar térmicamente fermentadores industriales y prototipos plásticos. Se ha constatado la alta heterogeneidad de las fermentaciones tanto intra-lote (amplitudes térmicas de hasta 8.5 ºC y temperaturas en algunos puntos de los fermentadores de 17 ºC) como inter-lote en fermentaciones sujetas a condiciones exógenas y endógenas muy variable

Optimización bayesiana multisolución para la exploración eficiente de agarres robóticos

[Resumen] El uso de brazos robóticos con agarre de tipo mano permite automatizar tareas previamente realizadas por humanos, minimizando la necesidad de acondicionar el entorno al brazo robótico. Esto es debido a la destreza y capacidad de manipulación que otorgan este tipo de agarres. Su aplicación es evidente: desde permitir un mayor grado de automatización en procesos industriales a incrementar la capacidad motriz de personas con discapacidades mediante sistemas asistenciales. No obstante, estas aplicaciones requieren con frecuencia manipular objetos previamente desconocidos, lo que en la práctica conlleva un sobre-coste elevado para reconfigurar y reprogramar el agarre del robot al nuevo objeto. A pesar de la existencia de simuladores que nos permite de manera eficiente evaluar y verificar que la configuración es válida para el agarre, automatizar la identificación del agarre sigue siendo un aspecto desafiante de la robótica. Por otro lado, en función de la tarea a realizar es posible que el agarre óptimo pueda impedir la manipulación, es por tanto necesario que el sistema sea multisolución, es decir, sea capaz de encontrar múltiples agarres alternativos lo suficientemente viables. En este trabajo se abordará la identificación automática de múltiples agarres para un objeto previamente desconocido mediante el uso de aprendizaje automático. Para ello, se evaluará en un simulador robótico una aproximación de prueba y error basada en la optimización bayesiana multisolución, la variante multisolución de un método de optimización global de caja negra

X chromosome inactivation does not necessarily determine the severity of the phenotype in Rett syndrome patients

Rett syndrome (RTT) is a severe neurological disorder usually caused by mutations in the MECP2 gene. Since the MECP2 gene is located on the X chromosome, X chromosome inactivation (XCI) could play a role in the wide range of phenotypic variation of RTT patients; however, classical methylation-based protocols to evaluate XCI could not determine whether the preferentially inactivated X chromosome carried the mutant or the wild-type allele. Therefore, we developed an allele-specific methylation-based assay to evaluate methylation at the loci of several recurrent MECP2 mutations. We analyzed the XCI patterns in the blood of 174 RTT patients, but we did not find a clear correlation between XCI and the clinical presentation. We also compared XCI in blood and brain cortex samples of two patients and found differences between XCI patterns in these tissues. However, RTT mainly being a neurological disease complicates the establishment of a correlation between the XCI in blood and the clinical presentation of the patients. Furthermore, we analyzed MECP2 transcript levels and found differences from the expected levels according to XCI. Many factors other than XCI could affect the RTT phenotype, which in combination could influence the clinical presentation of RTT patients to a greater extent than slight variations in the XCI pattern

X chromosome inactivation does not necessarily determine the severity of the phenotype in Rett syndrome patients

WOS: 000481590200024PubMed ID: 31427717Rett syndrome (RTT) is a severe neurological disorder usually caused by mutations in the MECP2 gene. Since the MECP2 gene is located on the X chromosome, X chromosome inactivation (XCI) could play a role in the wide range of phenotypic variation of RTT patients; however, classical methylation-based protocols to evaluate XCI could not determine whether the preferentially inactivated X chromosome carried the mutant or the wild-type allele. Therefore, we developed an allele-specific methylation-based assay to evaluate methylation at the loci of several recurrent MECP2 mutations. We analyzed the XCI patterns in the blood of 174 RTT patients, but we did not find a clear correlation between XCI and the clinical presentation. We also compared XCI in blood and brain cortex samples of two patients and found differences between XCI patterns in these tissues. However, RTT mainly being a neurological disease complicates the establishment of a correlation between the XCI in blood and the clinical presentation of the patients. Furthermore, we analyzed MECP2 transcript levels and found differences from the expected levels according to XCI. Many factors other than XCI could affect the RTT phenotype, which in combination could influence the clinical presentation of RTT patients to a greater extent than slight variations in the XCI pattern.Spanish Ministry of Health (Instituto de Salud Carlos III/FEDER) [PI15/01159]; Crowdfunding program PRECIPITA, from the Spanish Ministry of Health (Fundacion Espanola para la Ciencia y la Tecnologia); Catalan Association for Rett Syndrome; Fondobiorett; Mi Princesa RettWe thank all patients and their families who contributed to this study. The work was supported by grants from the Spanish Ministry of Health (Instituto de Salud Carlos III/FEDER, PI15/01159); Crowdfunding program PRECIPITA, from the Spanish Ministry of Health (Fundacion Espanola para la Ciencia y la Tecnologia); the Catalan Association for Rett Syndrome; Fondobiorett and Mi Princesa Rett

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data