Inf-SSM constrains the infinite-horizon evolution of SSMs via Grassmannian geometry and an efficient O(n^2) Sylvester solver to enable exemplar-free continual learning with reduced forgetting.
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D-Shap reformulates dynamic Shapley valuation as structured matrix maintenance exploiting utility and coalition locality to support millisecond task updates and orders-of-magnitude cheaper player updates.
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Exemplar-Free Continual Learning for State Space Models
Inf-SSM constrains the infinite-horizon evolution of SSMs via Grassmannian geometry and an efficient O(n^2) Sylvester solver to enable exemplar-free continual learning with reduced forgetting.
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Dynamic Shapley Computation
D-Shap reformulates dynamic Shapley valuation as structured matrix maintenance exploiting utility and coalition locality to support millisecond task updates and orders-of-magnitude cheaper player updates.