Loss reweighting is cast as an inverse problem that dynamically infers class weights to equalize per-class average losses under the Neural Collapse simplex ETF target.
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Rethinking Loss Reweighting for Imbalance Learning as an Inverse Problem: A Neural Collapse Point of View
Loss reweighting is cast as an inverse problem that dynamically infers class weights to equalize per-class average losses under the Neural Collapse simplex ETF target.