32nd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2022)

The 32nd MLSP is organizing the Data Challenge (DC) Sessions with new and exciting problems that aim at engaging signal processing and machine learning research community, industry, and practitioners. If you are planning to submit a Data Challenge proposal, please include:

• One-page call for participation
• Data Challenge Description
• Description of the dataset provided for training and evaluation criteria and methodology, guidelines for proponents, and submission deadline;
• List of potential participants.

Participation: Data Challenge organizers should facilitate participation, communication, and impact. Data Challenge organizers are not allowed to participate in the competition they are organizing.

Dataset: If applicable to the challenge, organizers are encouraged to provide at least one training dataset with both input and ground truth and one test dataset without the ground truth-the latter to be used for final assessment. A secondary test set for evaluation, which is not available to participants, is also encouraged to highlight the generalizability of their approach.

Evaluation: How the results are evaluated and ranked should be announced along with the challenge description. The evaluation methods should be unbiased and transparent to all participants. Provision of baseline approaches and evaluation metrics is encouraged.

DC Papers: Each challenge would have around 2-3 months to run the competition and rank/select winning teams. Each challenge can have up to 3 papers from the top ranked teams. The format should be consistent with MLSP regular paper.

• Organizers are responsible for coordinating the review of the challenge papers.
• The DC paper submission deadline should coincide with the model submission deadline for DCs.
• The DC paper acceptance announcement should coincide with the model evaluation results announcement.

DC Sessions: DC sessions will be organized in the MLSP 2022 program. This session will include DC paper presentations (oral or poster), followed by a panel or open discussion.