https://www.csc.kth.se/cvap/cvg/ml-seminars/tags/casual-machine-learning/ Recent content in Casual-Machine-Learning on KTH Machine Learning Seminars Hugo -- gohugo.io en-us © Copyright notice Thu, 08 Dec 2022 00:00:00 +0000 https://www.csc.kth.se/cvap/cvg/ml-seminars/posts/post-10/ Thu, 08 Dec 2022 00:00:00 +0000 https://www.csc.kth.se/cvap/cvg/ml-seminars/posts/post-10/ Title: Rhino: Deep Causal Temporal Relationship Learning with history-dependent noise Speaker: Wenbo Gong, Microsoft Research, Cambridge UK Date and Time: Thursday, December 8, 3-4 pm (2-3 pm GMT) Place: Zoom Meeting Meeting ID: 691 6539 9062 Abstract: Discovering causal relationships between different variables from time series data has been a long-standing challenge for many domains. Given the complexity of real-world relationships and the nature of observation in discrete time, the causal discovery method needs to consider non-linear relations between variables, instantaneous effects and history dependent noise. https://www.csc.kth.se/cvap/cvg/ml-seminars/posts/post-9/ Thu, 10 Nov 2022 00:00:00 +0000 https://www.csc.kth.se/cvap/cvg/ml-seminars/posts/post-9/ Title: Optimizing decisions with deep end-to-end causal inference Speaker: Agrin Hilmkil, Microsoft Research, Cambridge UK Date and Time: Thursday, November 10, 2-3 pm Place: Fantum, Lindstedtsvägen 24, Floor 5 Video Link: Zoom Meeting Meeting ID: 679 0294 8719 Abstract: In any type of decision making, the ability to predict the outcomes of different options will determine the quality of the decision made. However, traditional predictive models trained with supervised learning capture the biases of the underlying training data and are generally not robust to spurious correlations.