The ICML 2013 Workshop on Challenges in Representation Learning(1) 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.

Transient and CW spectroscopies unravel giant Rashba splitting in 2D hybrid perovskite multilayers.

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Abstract. The ICML 2013 Workshop on Challenges in Representation Learning3 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.

Recently the hybrid organic-inorganic trihalide perovskites have shown remarkable performance as active layers in photovoltaic and other optoelectronic devices. However, their spin characteristic properties have not been fully studied, although due to the relatively large spin-orbit coupling these materials may show great promise for spintronic applications. Here we demonstrate spin-polarized carrier injection into methylammonium lead bromide films from metallic ferromagnetic electrodes in two spintronic-based devices: a ‘spin light emitting diode’ that results in circularly polarized electroluminescence emission; and a ‘vertical spin valve’ that shows giant magnetoresistance. In addition, we also apply a magnetic field perpendicular to the injected spins orientation for measuring the ‘Hanle effect’, from which we obtain a relatively long spin lifetime for the electrically injected carriers. Our measurements initiate the field of hybrid perovskites spin-related optoelectronic applications.