Ben Hamner | Searcharxiv

arXiv2013

Observing Dark Worlds: A crowdsourcing experiment for dark matter mapping

We present the results and conclusions from the citizen science competition `Observing Dark Worlds', where we asked participants to calculate the positions of dark matter halos from 120 catalogues of simulated weak lensing galaxy data, using computational methods. In partnership with Kaggle (http://www.kaggle.com), 357 users participated in the competition which saw 2278 downloads of the data and 3358 submissions. We found that the best algorithms improved on the benchmark code, LENSTOOL by > 30% and could measure the positions of > 3x10^14MSun halos to less than 5'' and < 10^14MSun to within 1'. In this paper, we present a brief overview of the winning algorithms with links to available code. We also discuss the implications of the experiment for future citizen science competitions.

astro-ph.IM↗

arXiv2013

Challenges in Representation Learning: A report on three machine learning contests

The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions.

stat.ML↗