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Please contact us [makarand at cs dot toronto dot edu] if you have difficulties in registering. If you are from mainland China (and have a problem with the captcha) please email [yukun at cs dot toronto dot edu].

Terms and Conditions

The training data provided for each task may be used to train model parameters. The test data should be used strictly for reporting of results, i.e., it should not be used in any way to train or tune systems, for example, by evaluating multiple parameters or feature choices and reporting the best results obtained. It is the responsibility of the participant to divide the training set into appropriate training and validation splits, e.g., using 5-fold cross-validation. The tuned algorithms should then be run only once on the test data.

We strongly discourage multiple submissions to the server as the evaluation server should not be used for parameter tuning. The number of submissions for the same task is strictly controlled. If participants would like to report results in their papers for multiple versions of their algorithm (e.g., parameters or features) they can do so on a validation split of the training data and only submit the best performing setting for evaluation to our server. We enforce a minimum of 72 hours between submissions. If someone would like to submit earlier, e.g., due to a corrupt upload we kindly ask you to open a ticket for the same.

Users should not register multiple times using different email addresses. This also means that for collaborative effort across groups or within a lab, only one account should be used by all participants. Multiple accounts will be deleted and participants will be warned or black listed from future submissions. When registering, we ask all participants to provide their full name, institution affiliation and institutional email address (i.e., .edu). If you have any question regarding these policies, or wish to use a different email address please do not hesitate to get in touch with us!

By clicking on Register you agree to abide by the above terms and follow honest academic practices.