Targeted learning

We are the UK’s national institute for data science and artificial intelligence.The Institute is named in honour of Alan Turing, whose pioneering work in theoretical and applied mathematics, engineering and computing is considered to have laid the foundations for modern-day data science and artificial intelligence. The Institute’s goals are to undertake world-class research in data science and artificial intelligence, apply its research to real-world problems, driving economic impact and societal good, lead the training of a new generation of scientists, and shape the public conversation around data.Click here to join our newsletter

The Alan Turing Institute

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London School of Hygiene & Tropical Medicine

<p><strong>Turing ASG Lecture, as part of the Turing AI for Science and Government initiative</strong></p><p>Society is drowning in data and the current practice of learning from data is to apply traditional statistical methods that are too simplistic, arbitrarily chosen, and subject to manipulation. Nonetheless, these methods inform policy and science, affecting our sense of reality and judgements. This talk exposes this deceptive practice, and presents a solution — a principled and reproducible approach, termed targeted learning, for generating actionable and truthful information from complex, real-world data. This approach unifies causal inference, machine learning and deep statistical theory to answer causal questions with statistical confidence.</p><p>Find out more about our events on our <a href="http://www.turing.ac.uk/events" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">website</a>.</p><h2></h2><h3>About the speaker</h3><p><strong>Mark van der Laan</strong></p><p>Mark van der Laan, Ph.D., is a Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics (i.e., computational biology), survival analysis, censored data, targeted maximum likelihood estimation in semiparametric models, causal inference, data adaptive loss-based super learning, and multiple testing. Further details on Mark’s research interests are available here.</p>

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Targeted learning

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