3 papers
cs.LG2024
RESQUE: Quantifying Estimator to Task and Distribution Shift for Sustainable Model Reusability
Vishwesh Sangarya, Jung-Eun Kim
As a strategy for sustainability of deep learning, reusing an existing model by retraining it rather than training a new model from scratch is critical. In this paper, we propose R…
cs.CY2024
Estimating Environmental Cost Throughout Model's Adaptive Life Cycle
Vishwesh Sangarya, Richard Bradford, Jung-Eun Kim
With the rapid increase in the research, development, and application of neural networks in the current era, there is a proportional increase in the energy needed to train and use…
cs.LG2024
Aggregate Representation Measure for Predictive Model Reusability
Vishwesh Sangarya, Richard Bradford, Jung-Eun Kim
In this paper, we propose a predictive quantifier to estimate the retraining cost of a trained model in distribution shifts. The proposed Aggregated Representation Measure (ARM) qu…