A proximal gradient sampler for composite log-concave distributions achieves near-optimal iteration complexity of order kappa sqrt(d) log^4(1/epsilon) in total variation distance under strong convexity and smoothness.
Structured logconcave sampling with a restricted
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
method 1
citation-polarity summary
fields
math.ST 1years
2026 1verdicts
UNVERDICTED 1roles
method 1polarities
use method 1representative citing papers
citing papers explorer
-
A proximal gradient algorithm for composite log-concave sampling
A proximal gradient sampler for composite log-concave distributions achieves near-optimal iteration complexity of order kappa sqrt(d) log^4(1/epsilon) in total variation distance under strong convexity and smoothness.