Welcome to Phase 2 for prescreened participants! Help unlock the potential of privacy-enhancing technologies (PETs) to combat global societal challenges. Develop efficient, accurate, and extensible federated learning solutions with strong privacy guarantees for individuals in the data.
Quick Facts
Participants
No. of Entries
Prize
Winner
Faculty Science Limited
1st Place TeamNavigation
Leaderboard
NOTE: This leaderboard ranks teams by model AUPRC score and does not reflect the final rankings based on overall evaluation criteria. Please see the winners announcement for the final winner rankings.
Average Precision for Partitioning Scenario N1: Average Precision (AP), also equivalent to area under the precision–recall curve (AUPRC or PRAUC) with no interpolation, ranges from 0 to 1. For more information, see sklearn's documentation. The goal is to maximize AP. In the case of multilabel classification, this metric will be calculated as a macro-average, with the final metric being an unweighted mean of AP values calculated for each label separately.
Average Precision for Partitioning Scenario N2: Average Precision (AP), also equivalent to area under the precision–recall curve (AUPRC or PRAUC) with no interpolation, ranges from 0 to 1. For more information, see sklearn's documentation. The goal is to maximize AP. In the case of multilabel classification, this metric will be calculated as a macro-average, with the final metric being an unweighted mean of AP values calculated for each label separately.
Average Precision for Partitioning Scenario N3: Average Precision (AP), also equivalent to area under the precision–recall curve (AUPRC or PRAUC) with no interpolation, ranges from 0 to 1. For more information, see sklearn's documentation. The goal is to maximize AP. In the case of multilabel classification, this metric will be calculated as a macro-average, with the final metric being an unweighted mean of AP values calculated for each label separately.
U.K. PETs Prize Challenge: Phase 2 (Pandemic Forecasting–Federated): Rules and Terms of Data Use
By participating in this challenge, I acknowledge that I have read, understood, and accept DrivenData’s privacy and terms of use policies expressed on this website, as well as the UK Privacy Enhancing Technologies Prize Challenge rules, terms and conditions found at the Innovate UK challenge website.
Additionally, I acknowledge that I signed the relevant UVA/SWIFT data use agreements in order to participate in Phase 1, and remain subject to the conditions given therein, the terms and conditions of which are provided in Annex A of the relevant technical briefs - Financial Crime Prevention Technical Brief and Pandemic Forecasting and Response Technical Brief.