ICML 2020 Announces Outstanding Paper Awards


Organizers of the 37th International Conference on Machine Learning (ICML) have announced their Outstanding Paper awards, recognizing papers from the current conference that are “strong representatives of solid theoretical and empirical work in our field.”

A total of 1,088 papers out of 4,990 submissions made it to the prestigious machine learning conference. The acceptance rate of 21.8 percent is slightly lower than 2019’s 22.6 percent (774 accepted papers from 3,424 submissions), and it seems likely the drastic increase in submissions helped contribute to this.

Visión electrónica

Focus and Scope

In 2007, during the second half of the year, a group of academic staff including various students working for the Faculty of Technological Studies at Universidad Distrital Francisco Jos´e de Caldas perceived the necessity to build a serial publication intended for the circulation of research results in topics of the large area of engineering and technology; in thematic area of Electrical, Electronics and computing; and in the disciplines of electrical and electronic engineering, robotics and automatic control, automation and control systems, engineering systems and communications, telecommunications, and Hardware and computer architecture; as well as basic and related sciences.

https://revistas.udistrital.edu.co/index.php/visele/about

About Artificial Intelligence-2020 Webinar

Webinars on Artificial Intelligence, Automation and Robotics will be held during August 26-27, 2020 at Dubai, UAE. This Live Webinar will unite Computer Engineers, driving analysts, researchers and scientists in the area of interest from all over the world, which would provide a platform to discuss and exchange of ideas and exploration of future research avenues in various fields of Artificial Intelligence, Automation & Robotics.

https://www.meetingsint.com/conferences/artificialintelligence

Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?

Deep Learning sits at the forefront of many important advances underway in machine learning. With backpropagation being a primary training method, its computational inefficiencies require sophisticated hardware, such as GPUs. Learn about this recent breakthrough algorithmic advancement with improvements to the backpropgation calculations on a CPU that outperforms large neural network training with a GPU.

https://www.kdnuggets.com/2020/03/deep-learning-breakthrough-sub-linear-algorithm-no-gpu.html