Year: 2017

MPhil-PhD transfer presentation When: Thu, 30 Nov 2017, 12noon Where: EM01 Who: Simon Odense, City, University of London Title: Compact Rule Extraction from Probabilistic Neural Networks Abstract: I will discuss new techniques for extracting M-of-N rules from restricted Boltzmann machines. I will begin by discussing rule extraction and its importance for explainable AI before describing…Continue Reading MPhil-PhD transfer – Simon Odense – 30 Nov, 12noon, EM01

Machine Learning seminar When: Fri, 20 Oct 2017, 1pm Where: AG24a, College Building Who: Alessandro Abate, University of Oxford Title: Data-driven and model-based quantitative verification of physical systems Abstract: In this seminar I discuss a new and formal, measurement-driven and model-based automated verification technique, to be applied on quantitative properties over systems with partly unknown…Continue Reading ML seminar, Fri 20 Oct, 1pm

MPhil-PhD transfer presentation Dan Philps Thursday, 21 September 2017, 2pm Room: A109 (College building) Title: Motif Memory Nets Abstract: Motifs are recurring patterns in time-series data that have the power to explain or forecast future events/data points. In the context of lifelong learning of a time-continuous dataset, “motif awareness” would improve modelling accuracy when compared…Continue Reading MPhil-PhD transfer seminar – Dan Philps

Machine Learning Seminar Thursday, 1 June, 2pm, ELG10 Jakob Foerster (University of Oxford) Title: Counterfactual Multi-Agent Policy Gradients Abstract: Cooperative multi-agent systems can be naturally used to model many real world problems, such as network packet routing or the coordination of autonomous vehicles. There is a great need for new reinforcement learning methods that can efficiently…Continue Reading ML Seminar: Thu, 1 June, 2pm, ELG10, Jakob Foerster (University of Oxford)

ML seminar Kaio Motawara When: 15 May 2017, 1pm Where: AG10   Abstract: Appropriate feature engineering, the process of combining and transforming raw features, can contribute significantly to improving the performance of a supervised learning task. Because of the combinatorial explosion of possible engineered features, very often successful feature engineering in a corporate environment requires domain…Continue Reading ML Seminar: 15 May 2017, 1pm, AG10

Machine Learning seminar Prof Duncan Gillies, Imperial College London Monday, 20 March 2017, 2pm. College Building, room AG22 Title: Visual Cognition in Face Recognition (work by C. E. Thomaz, V. Amaral, G. A. Giraldi, D. F. Gillies and D. Rueckert) Abstract: Recently new methods have been emerging in the field of image recognition. In particular,…Continue Reading Machine Learning seminar by Prof Duncan Gillies, Imperial College

The 12th edition of the Workshop on Neural-Symbolic Learning and Reasoning will take place at City, University of London, on 17 and 18 July 2017. The workshop studies the combination of well-founded symbolic AI with robust neural computing to help tackle data-driven challenges in many areas of application, from health to finance, transport and global business….Continue Reading 12th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy’17) at City, University of London, 17-18 July 2017