Efficient Online Inverse Optimization with $O(d)$ Regret
This work builds on the variable-metric framework of Sakaue et al., adding a self-normalized rank-one update, and replaces the $\log\det$ potential by the trace power $\tr(H^{-1/2})$, which is bounded outright and removes the $\ln T$.
Yang Cai, Anupam Gupta, Vineet Gupta et al.
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