Punto informativo donde se estará dando información detallada de nuestras actividades como: Proyecto de Robótica Competencia de Programación internacional Congreso Centroamericano CONESCAPAN 2023-Guatemala Conferencia sobre IA Visita técnica a GBM Justo en la entrada del edificio de B2 Universidad Autonoma de Honduras, tegucigalpa, Francisco Morazan, Honduras, 11101

Bootcamp parte de la iniciativa de LatinPractice, los participantes diseñaran sus propios ASICS para ser fabricados por Skywater Technologies, aplicando todo el proceso real de VLSI. Tecnológico de Costa Rica, Campus Central, Cartago, Cartago, Costa Rica

Webinar informativo y practico con Google Colab, donde puedan resolver un problema de clasificacion de textos mediante python. Virtual: https://events.vtools.ieee.org/m/368308

Estado del evento Programa del evento Students y Travel grants Agenda: Estado del evento Programa del evento Students y Travel grants Virtual: https://events.vtools.ieee.org/m/369177

Hablaremos sobre la importancia de la estandarización 5G, que permite una conectividad global más fluida y la interoperabilidad entre diferentes redes. Además, tocaremos el tema de "New Radio", una tecnología inalámbrica de banda ancha que ofrece velocidades de transmisión súper rápidas y una experiencia del usuario sin precedentes. Por último, se explicará sobre el "Nex Generation Core", el corazón de la red 5G, que gestiona el tráfico de datos y habilita características avanzadas para mejorar nuestra vida digital Virtual: https://events.vtools.ieee.org/m/369666

In this talk we discuss approaches for distributed machine learning (ML) in wireless networks, in particular vehicular networks and resource-constrained Internet of Things (IoT) networks. Federated Learning (FL) and Split Learning (FL) are popular approaches in such environments. First, we present Early Exit of Communication (EEoC), which adaptively splits ML inference in an IoT edge computing environment to meet latency and energy constraints. This layer-based (vertically partitioned) approach has been extended by Distributed Micro-Split Deep Learning in Heterogeneous Dynamic IoT (DISNET), which adds horizontal partitioning to better support flexible, distributed, and parallel execution of neural network models on heterogeneous IoT devices under dynamic conditions. Then, we also consider the training aspect by developing and evaluating Adaptive REsource-aware Split-learning (ARES), a scheme for efficient model training in IoT systems. Recent work suggests Dynamic FL (DFL) for heterogeneous IoT, which uses resource-aware SL and FL based on similarity-based layer-wise model aggregation. Co-sponsored by: Universidad Tecnológica de Panamá Speaker(s): Torsten Braun Agenda: Registro de participantes Conferencia Preguntas y respuestas Despedida Room: Salón Roberto Barraza, Bldg: Edificio 1, Salón Roberto Barraza, Universidad Tecnológica de Panamá, Campus Víctor Levi Sasso, Panama, Panama, Panama

The IEEE Nano Peru colloquia are part of the scientific activities promoted by the Peru Chapter of the IEEE Nanotechnology Council in order to disseminate the scientific work currently being developed in the area of nanoscience and nanotechnology. For the realization of these regular events there are guests of recognized scientific trajectory. (These talks will be given in Spanish) Speaker(s): Poma, Champi Bldg: Auditorio del Instituto de Física. Universidad Nacional Mayor de San Marcos, Calle Germán Amézaga 375., Lima, Lima, Peru, Virtual: https://events.vtools.ieee.org/m/370378