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. Analysis covers preprocessing, assembly of DNA fragments into complete genomes, imputation of missing data, filtering of bad data, prediction of the meaning of the DNA in individual cells, compression
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(e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects of machine learning such as
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inference and deployment costs (e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects
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