Blog – Page 3 – Wilmar Igl, PhD

Facial feature representation: The Code for Facial Identity in the Primate Brain

The following paper is a breakthrough in facial feature recognition and numeric representation of facial features and may be helpful to understand the genomic basis of facial features (once the relevant dimensions of the phenome are identified), but also to help to recognize the emotional expression in human faces [1,2]. [1] http://www.cell.com/cell/fulltext/S0092-8674(17)30538-X [2] http://www.bbc.co.uk/news/science-environment-4013124

2017-06-10wiliglhealth and disease

KAGGLE competition on Zillow’s Home Value Prediction ($1,200,000 Prize Money)

KAGGLE’s newest predictive analytics competition on improving the Zillow’s Home Value Prediction with an overall prize money of $1,200,000 is currently the talk of the town and has attracted 716 teams ·(7 months to go, 4 months to go until merger deadline) [1]. Are you interested in joining my team? [1] https://www.kaggle.com/c/zillow-prize-1/data

2017-06-10wiligldata, statistics

Inspiring talk by David Spiegelhalter at PSI 2017, London

David Spiegelhalter gave inspiring and entertaining talk on “Engaging without manipulating: the balanced communication of statistics” at PSI 2017 conference in London. Obviously, scientific results are often miscommunicated by mass media to boost the novelity and relevance of scientific results. After David’s talk I raised the question whether addressing the questions who owns the results…

2017-05-17wiligldont know

Rstudio Connect for deployment of software and reports

Rstudio has recently released (2017-01) their Rstudio connect platform for deployment of software and reports, which I am currently evaluating: Quote: RStudio Connect is a new publishing platform for the work your teams create in R. Share Shiny applications, R Markdown reports, dashboards, plots, and more in one convenient place. Use push-button publishing from the…

2017-03-07wiligldont know

Bayesian Belief Networks and AgenaRisk

I recently got my hands on Bayesian Belief Networks to model multi-dimensional decision problems, which include objective and subjective data (“beliefs”) with varying degrees of under uncertainty. To choose a (non)trivial example one can look at the question “Does she/he like me?” after you met this attractive person, randomly picking the same book on machine…

2017-03-07wiligldont know

Gradient Boosting Elections / Conditional demographic elections

Considering the success in of Gradient boosting machines in machine learning, one might think of the application of the same principle to elections. The rationale behind it being that voters may have changed their vote conditioned on the knowledge of the current power distribution is. Unconditional voting may lead to power distributions which may be…

2016-10-08wiliglpolitics

Estimands – What should they be? What can they be?

If you want to find out, that you share quite a lot of confusion regarding the estimand concept with the RSS/PSI experts, I recommend listening to the audio recording of the RSS/PSI journal club on estimands from 2016-07-06 on YouTube [1]. Personally, I think that much of the confusion around the estimand concept (except not…

2016-10-01wiligldont know

Gradient Boosting Machines

Gradient Boosting Machines as a family of methods have been the “talk of the town” in the Machine learning world for a while now, with the specific flavour of Gradient Boosting Trees has been regarded as “the best off-the-shelf” classifier in the world” (Breiman, 1986/1987, see Hastie et al. 2013) [1]. A wonderful review about…

2016-10-01wiliglstatistics

Science’s 1%: How income inequality is getting worse in research

A critical NATURE article about income inequality across academic career levels focused wage distribution in California, US [1]. I would like to see this also in the context of great poverty of students at the University of California, Los Angeles, USA, [2], but also poor students at German Universities [3]. After experiencing myself that I…

2016-10-01wiliglpolitics

Paul Wick’s inspirational talk about PatientsLikeMe at PSI 2016 in Berlin

It was total pleasure to listen to Paul Wick’s (VP of Innovation at PLM) talk [1] about the PatientsLikeMe platform. Major learnings for me were: the enormous increased potential for patients in clinical trials to unblind themselves by exchanging info on their experiences on the treatment (eg side effects) . the enormous creativity of patients…

2016-05-26wiliglresearch infrastructure