Humans have the extraordinary ability to learn continually from experience. Not only can we apply previously learned knowledge and skills to new situations, we can also use these as the foundation for later learning. One of the grand goals of AI is building an artificial continually learning agent that constructs a sophisticated understanding of the world from its own experience through the autonomous incremental development of ever more complex skills and knowledge.
“Continual Learning” (CL) is indeed a fast emerging topic in AI concerning the ability to efficiently improve the performance of a deep model over time, dealing with a long (and possibly unlimited) sequence of data/tasks. In this workshop, after a brief introduction of the topic, we’ll implement different Continual Learning strategies and assess them on common vision benchmarks. We’ll conclude the workshop with a look at possible real world applications of CL.
Vincenzo Lomonaco is a Deep Learning PhD student at the University of Bologna and founder of ContinualAI.org. He is also the PhD students representative at the Department of Computer Science of Engineering (DISI) and teaching assistant of the courses “Machine Learning” and “Computer Architectures” in the same department. Previously, he was a Machine Learning software engineer at IDL in-line Devices and a Master Student at the University of Bologna where he graduated cum laude in 2015 with the dissertation “Deep Learning for Computer Vision: a Comparison Between CNNs and HTMs on Object Recognition Tasks”.
The venue has a limited seating capability, please be considerate and cancel your order if you are not willing to attend so that someone from the waitlist will be able to participate.
18.30 Doors opening
19:00 Data Science Milan community introduction
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About the host:
MIKAMAI is a leading IT consultancy and development agency in Italy. MIKAMAI has earned its dominant reputation for delivering real value to our clients and being leading innovators in emerging technologies in web and mobile solutions and products of the Internet of Things. We work with different languages and technologies, including but not limited to Ruby (and Ruby/Rails), React, AngularJS, Elixir, Redis and PostgreSQL. We tend to work with containers in mind (we are huge docker fans) and we consider ourselves AWS experts.