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TIGER: Tunable-Geometry Accelerated Gradient Sliding with Adaptive Safeguards under Similarity
We study distributed composite optimization under function similarity when synchronized gradient queries dominate local computation. We propose TIGER, an accelerated gradient-sliding method in problem-adapted Bregman geometry. The method applies to constrained non-Euclidean domains, allows the commu
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