- "After an exciting 60 days with over 15 different teams leading the pack, the Merck Molecular Activity Challenge has closed and the winners have been verified. The first place prize of $22,000 goes to ‘gggg,’ a team of academics hailing from the University of Toronto and the University of Washington with expertise in defining the state-of-the-art in machine learning..." [See the full story from the competition website here.] The objective of the Kaggle competition was to identify the best statistical techniques for predicting biological activities of different molecules, both on- and off-target, given numerical descriptors generated from their chemical structures.
The winning team included George Dahl (DCS), Ruslan Salakhutdinov (DCS/Stats), Navdeep Jaitly (DCS), Chris Jordan-Squire (UW), and Geoffrey Hinton (DCS).
- This great news comes on the heels of another win: Team 'SuperVision', made up of PhD students Alex Krizhevsky, grad (now Stanford postdoc) Ilya Sutskever, with Geoffrey Hinton, won the ImageNet Large Scale Visual Recognition Challenge this fall. The goal of this competition was to estimate the content of photographs for the purpose of retrieval and automatic annotation using a subset of the large hand-labeled ImageNet dataset (10,000,000 labeled images).
See more information on the ImageNet accomplishment here.
Both of these competitions are entered by the top minds in the field, worldwide.