Papers › Accelerated Bregman Proximal Gradient Methods for Relatively Smooth Convex Optimization

Accelerated Bregman Proximal Gradient Methods for Relatively Smooth Convex Optimization

9 Aug 2018arXiv:1808.03045links table onlyarchive 2025-07-28

Filip Hanzely, Peter Richtarik, Lin Xiao

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We consider the problem of minimizing the sum of two convex functions: one is differentiable and relatively smooth with respect to a reference convex function, and the other can be nondifferentiable but simple to optimize. We investigate a triangle scaling property of the Bregman distance generated by the reference convex function and present accelerated Bregman proximal gradient (ABPG) methods that attain an O(k^(-γ)) convergence rate, where γ∈(0,2] is the triangle scaling exponent (TSE) of the Bregman distance. For the Euclidean distance, we have γ=2 and recover the convergence rate of Nesterov's accelerated gradient methods. For non-Euclidean Bregman distances, the TSE can be much smaller (say γ≤1), but we show that a relaxed definition of intrinsic TSE is always equal to 2. We exploit the intrinsic TSE to develop adaptive ABPG methods that converge much faster in practice. Although theoretical guarantees on a fast convergence rate seem to be out of reach in general, our methods obtain empirical O(k⁻²) rates in numerical experiments on several applications and provide posterior numerical certificates for the fast rates.

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Microsoft/accbpg officialmentioned in papermentioned on GitHubMIT report
linxiaolx/accbpg officialmentioned in papermentioned on GitHub report

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ABPG linxiaolx/accbpg/accbpg/algorithms.py official repository ran · fixture could not drive it MIT (permissive) · 9a55fc3fd11346ec · report
BPG linxiaolx/accbpg/accbpg/algorithms.py official repository ran · fixture could not drive it MIT (permissive) · 70d648a19e9e5f2a · report
solve_theta linxiaolx/accbpg/accbpg/algorithms.py official repository ran · honoured contract fingerprinted MIT (permissive) · 5aabc13a3b3cb060 · report
D_opt_FW Microsoft/accbpg/accbpg/D_opt_alg.py official repository unverified MIT (permissive) · 6d3542f113696500 · report
D_opt_FW_away Microsoft/accbpg/accbpg/D_opt_alg.py official repository unverified MIT (permissive) · ebb43079607596cc · report
D_opt_KYinit Microsoft/accbpg/accbpg/applications.py official repository unverified MIT (permissive) · 87864de3167417a5 · report
D_opt_design Microsoft/accbpg/accbpg/applications.py official repository unverified MIT (permissive) · 5ff255477435bde3 · report
D_opt_libsvm Microsoft/accbpg/accbpg/applications.py official repository unverified MIT (permissive) · 0779cc54868c0714 · report
load_libsvm_file Microsoft/accbpg/accbpg/utils.py official repository unverified MIT (permissive) · 8097e49b7557dfbf · report
mnist_2digits Microsoft/accbpg/accbpg/utils.py official repository unverified MIT (permissive) · 39b1e2f7bd6e45fb · report
shuffle_data Microsoft/accbpg/accbpg/utils.py official repository unverified MIT (permissive) · fb69d5f3793a0e5b · report

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