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Sydney Machine Learning is about getting together to discuss all fields and implementations of machine learning, machine learning's current and future impact and a place to share your work on machine learning and learn from others.

Upcoming events (1)

DSAi: Symbolic Ai Special Edition @ Amazon Web Services

Amazon Web Services

DSAi: Symbolic Ai Special Edition @ Amazon Web Services PLEASE NOTE: that RSVPing to this page DOES NOT GRANT YOU ACCESS to this meetup, Spaces are limited! Due to popular demand & Amazon Facilities Management, PLEASE SIGNUP for A TICKET via the EVENTBRITE LINK BELOW: >>CLICK EVENTBRITE LINK BELOW<< - https://www.eventbrite.com.au/e/dsai-symbolic-ai-special-edition-tickets-58337658507 __________________________________________________ DESCRIPTION Amazon Web Services and the Data Science and Ai Association of Australia presents our Symbolic Ai special edition event. Come along to learn from renowned industry leaders on the practical limits on what computers can and cannot do & how a million-dollar challenge might be solved using Symbolic Ai and Computational complexity theory. ~ Professor Claude Sammut Combining Symbolic and Sub-Symbolic AI for Robot Learning Machine learning has had many recent successes, but current popular methods have their limitations, including requiring many training examples and a lack of transparency. Classical AI techniques can help to learn from a small number of examples and make the result more explainable. In particular, classical AI has well-developed methods for representing and reasoning about background domain knowledge. In this talk, we describe the hybrid learning methods we have used in robot learning that combine symbolic learning and planning with numerical methods. Examples of such robot learning systems include learning a bipedal walk, a robot learning to use tools and a rescue robot learning to traverse rough terrain. Professor Maurice Pagnucco, the Head of the School of Computer Science and Engineering at UNSW will talk about computational complexity theory - one of the most popular topics in computer science today. Computational complexity theory focuses on classifying computational problems according to their inherent difficulty and relating these classes of problems to each other. Did you know that computational complexity theory can help you solve one of 7 Millennium Prize institute Problems? A correct solution to any of the problems will result in a US$1 million prize being awarded by the institute to the discoverer(s). ___________________________________________________________ Biography of presenters Professor Maurice Pagnucco Professor Maurice Pagnucco is Deputy Dean (Education), Engineering and the Head of the School of Computer Science and Engineering at UNSW. Maurice graduated with a BSc (Hons I) and PhD from the University of Sydney. He has held academic positions at the University of Sydney, Macquarie University, the University of Toronto and the University of New South Wales. His research interests lie in: Knowledge Representation and Reasoning Cognitive Robotics Belief Change Reasoning About Actions Claude Sammut is a Professor in the School of Computer Science and Engineering, University of New South Wales. His did pioneering work in Behavioural Cloning. His current interests are focussed on Machine Learning applications in Robotics. He was the leader of the UNSW teams that won RoboCup four-legged robot competitions in 2000, 2001 and 2003; the winners of the 2014 and 2015 Standard Platform League and the team that won the award for best autonomous robot at RoboCup Rescue 2009, 2010 and 2011. In 2012, he was elected to the board of trustees of the RoboCup Federation having previously served as a member of the executive committee from 2003 to 2009. He is co-editor-in-chief of Springer's Encyclopedia of Machine Learning and Data Mining and general chair of RoboCup 2019, Sydney. Schedule 6:00 - 6:30: Beer, Pizza, Networking 6:30 - 6:40: Intro 6:40 - 7:10: Prof. Maurice Pagnucco Talk 7:10 - 7:20: Small break 7:20 - 7:50 Prof. Claude Sammut Talk 7:50 - 8:15 QnA 8:15 - 8:30 Wrap up

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