A Unified Framework for Iterate Convergence of Bregman Proximal Methods | Paper Citation Record

Observation 3cea62f9-0874-459a-b5b9-a39526980f9f · outbound

This paper cites Convergence of the iterates of descent methods for analytic cost functions.SIAM Journal on Optimization, 16(2): 531–547, 2005.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Convergence of the iterates of descent methods for analytic cost functions.SIAM Journal on Optimization, 16(2): 531–547, 2005

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.567572Z

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This paper cites Hessian Riemannian gradient flows in convex programming.SIAM Journal on Control and Optimization, 43(2):477–501, 2004.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Hessian Riemannian gradient flows in convex programming.SIAM Journal on Control and Optimization, 43(2):477–501, 2004

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.555639Z

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This paper cites Hessian Riemannian gradient flows in convex programming.SIAM Journal on Control and Optimization, 43:477–501, 2018.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Hessian Riemannian gradient flows in convex programming.SIAM Journal on Control and Optimization, 43:477–501, 2018

Reference 3

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Observation cd5a699d-0e1c-4577-91fb-b08d6158ee1a · outbound

This paper cites Regularized Lotka-Volterra dynamical system as continuous proximal-like method in optimization.Journal of Optimization Theory and Applications, 121:541–570, 2004.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Regularized Lotka-Volterra dynamical system as continuous proximal-like method in optimization.Journal of Optimization Theory and Applications, 121:541–570, 2004

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.533166Z

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A Unified Framework for Iterate Convergence of Bregman Proximal Methods Unresolved cited work

Reference 5

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This paper cites The rate of convergence of Bregman proximal methods: Local geometry versus regularity versus sharpness.SIAM Journal on Optimization, 34(3):2440–2471, 2024.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods The rate of convergence of Bregman proximal methods: Local geometry versus regularity versus sharpness.SIAM Journal on Optimization, 34(3):2440–2471, 2024

Reference 6

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This paper cites Fast composite optimization and statistical recovery in federated learning.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Fast composite optimization and statistical recovery in federated learning

Reference 7

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This paper cites Bauschke, Jérôme Bolte, and Marc Teboulle.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Bauschke, Jérôme Bolte, and Marc Teboulle

Reference 8

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Reference 9

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This paper cites MOS-SIAM Series on Optimization.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods MOS-SIAM Series on Optimization

Reference 10

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This paper cites Mirror descent and nonlinear projected subgradient methods for convex optimization.Operations Research Letters, 31(3):167–175, 2003.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Mirror descent and nonlinear projected subgradient methods for convex optimization.Operations Research Letters, 31(3):167–175, 2003

Reference 11

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Observation d00a0bc6-9d98-4b89-9609-5c52d9800429 · outbound

This paper cites Barrier operators and associated gradient-like dy- namical systems for constrained minimization problems.SIAM Journal on Control and Optimization, 42:1266–1292, 2003.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Barrier operators and associated gradient-like dy- namical systems for constrained minimization problems.SIAM Journal on Control and Optimization, 42:1266–1292, 2003

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.465769Z

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This paper cites Barrier operators and associated gradient-like dy- namical systems for constrained minimization problems.SIAM journal on control and optimization, 42(4):1266–1292, 2003.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Barrier operators and associated gradient-like dy- namical systems for constrained minimization problems.SIAM journal on control and optimization, 42(4):1266–1292, 2003

Reference 13

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This paper cites The Łojasiewicz inequality for nons- mooth subanalytic functions with applications to subgradient dynamical systems.SIAM Journal on Optimization, 17(4):1205–1223, 2007.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods The Łojasiewicz inequality for nons- mooth subanalytic functions with applications to subgradient dynamical systems.SIAM Journal on Optimization, 17(4):1205–1223, 2007

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.447992Z

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Observation e252b294-65cd-4e58-aa06-f4a7ba58f46d · outbound

This paper cites Clarke subgradients of stratifiable functions.SIAM Journal on Optimization, 18(2):556–572, 2007.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Clarke subgradients of stratifiable functions.SIAM Journal on Optimization, 18(2):556–572, 2007

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.436785Z

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Observation 147eee1e-ac43-4101-8b76-523d96ee3b44 · outbound

This paper cites First order methods beyond convexity and Lipschitz gradient continuity with applications to quadratic inverse problems.SIAM Journal on Optimization, 28(3):2131–2151, 2018.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods First order methods beyond convexity and Lipschitz gradient continuity with applications to quadratic inverse problems.SIAM Journal on Optimization, 28(3):2131–2151, 2018

Reference 16

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This paper cites Hessian barrier algorithms for linearly constrained optimization problems.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Hessian barrier algorithms for linearly constrained optimization problems

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.418735Z

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Reference 18

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Observation dd1e3638-5efc-44b7-9643-a3d10e4f50f3 · outbound

This paper cites Sparse and stable markowitz portfolios.Proceedings of the National Academy of Sciences, 106(30):12267–12272, 2009.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Sparse and stable markowitz portfolios.Proceedings of the National Academy of Sciences, 106(30):12267–12272, 2009

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.401062Z

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Observation 8ac0f33e-978f-475e-8099-f31d317ef955 · outbound

This paper cites Convex Optimization: Algorithms and Complexity.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Convex Optimization: Algorithms and Complexity

Reference 20

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This paper cites The developments of proximal point algorithms.Journal of the Operations Research Society of China, 10(2):197–239, 2022.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods The developments of proximal point algorithms.Journal of the Operations Research Society of China, 10(2):197–239, 2022

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.390260Z

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This paper cites Robust uncertainty princi- ples: Exact signal reconstruction from highly incomplete frequency information.IEEE Transactions on Information Theory, 52(2):489–509, 2006.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Robust uncertainty princi- ples: Exact signal reconstruction from highly incomplete frequency information.IEEE Transactions on Information Theory, 52(2):489–509, 2006

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.378521Z

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Observation 161bdd4d-3375-40ca-9bf6-c19c6cc3a3ed · outbound

This paper cites Proximal minimization algorithm with D- functions.Journal of Optimization Theory and Applications, 73(3):451–464, 1992.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Proximal minimization algorithm with D- functions.Journal of Optimization Theory and Applications, 73(3):451–464, 1992

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.367264Z

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Observation 8130e0e7-db62-400b-9538-b6caa99dbe1e · outbound

This paper cites Convergence analysis of a proximal-like minimization algorithm using Bregman functions.SIAM Journal on Optimization, 3(3):538–543, 1993.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Convergence analysis of a proximal-like minimization algorithm using Bregman functions.SIAM Journal on Optimization, 3(3):538–543, 1993

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.355965Z

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Observation bd213bdc-957a-4571-9cfe-78f672721347 · outbound

This paper cites On the Iterate Convergence of Bregman Projected Gradient Method.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods On the Iterate Convergence of Bregman Projected Gradient Method

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-08T11:35:12.878626Z

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Observation 9ad8222a-0854-4bd9-aa22-dc8ecc2f5350 · outbound

This paper cites Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Spurious Stationarity and Hardness Results for Bregman Proximal-Type Algorithms

Reference 26

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This paper cites On The Linear Convergence of Bregman Proximal Gradient Methods with Applications to Kullback--Leibler regression.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods On The Linear Convergence of Bregman Proximal Gradient Methods with Applications to Kullback--Leibler regression

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-08T11:35:12.852367Z

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This paper cites Norm preserving extension of convex Lipschitz functions.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Norm preserving extension of convex Lipschitz functions

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.343999Z

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Observation 45befb39-22c6-481a-b46d-ed2e27a29770 · outbound

This paper cites Institut de Recherche Mathé- matiques de Rennes, 1999.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Institut de Recherche Mathé- matiques de Rennes, 1999

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.332221Z

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Reference 30

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This paper cites Stochastic subgra- dient method converges on tame functions.Foundations of Computational Mathematics, 20(1):119–154, 2020.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Stochastic subgra- dient method converges on tame functions.Foundations of Computational Mathematics, 20(1):119–154, 2020

Reference 31

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This paper cites A gen- eralized approach to portfolio optimization: Improving performance by constraining portfolio norms.Management Science, 55(5):798–812, 2009.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods A gen- eralized approach to portfolio optimization: Improving performance by constraining portfolio norms.Management Science, 55(5):798–812, 2009

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.303058Z

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Observation 200ae0e2-9f2b-4745-82f0-397774baa5a1 · outbound

This paper cites On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-08T11:35:12.836527Z

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Observation e42935e9-216b-413a-a355-a8e32639d8fb · outbound

This paper cites Stochastic Bregman subgradient methods for nonsmooth nonconvex optimization problems.Journal of Optimization Theory and Applications, 206(3):67, 2025.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Stochastic Bregman subgradient methods for nonsmooth nonconvex optimization problems.Journal of Optimization Theory and Applications, 206(3):67, 2025

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.291966Z

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Observation 6c28f261-6c1b-44e2-80fe-6b81a4f9b7f6 · outbound

This paper cites Non-KKT Accumulation in Entropic Mirror Descent.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Non-KKT Accumulation in Entropic Mirror Descent

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-08-08T11:35:12.819282Z

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This paper cites Compressed sensing.IEEE Transactions on Information Theory, 52 (4):1289–1306, 2006.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Compressed sensing.IEEE Transactions on Information Theory, 52 (4):1289–1306, 2006

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.280847Z

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Observation ae6dede6-817a-4157-a402-0d58592dfa0e · outbound

This paper cites Chapman and Hall/CRC, 2025.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Chapman and Hall/CRC, 2025

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.269481Z

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Observation a812e652-4fe3-4edf-b14b-755653bb1dab · outbound

This paper cites Springer, New York, 2003.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Springer, New York, 2003

Reference 38

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Observation 87227a5b-a242-41ec-bd64-b01e4f24e78a · outbound

This paper cites Central paths, generalized proximal point methods, and cauchy trajectories in Riemannian manifolds.SIAM Journal on Control and Optimization, 37(2):566–588, 1999.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Central paths, generalized proximal point methods, and cauchy trajectories in Riemannian manifolds.SIAM Journal on Control and Optimization, 37(2):566–588, 1999

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.252039Z

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Observation 2eea8738-7497-4b67-9969-a8a8f32acdc8 · outbound

This paper cites Non-Convex Optimization for Machine Learning.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Non-Convex Optimization for Machine Learning

Reference 40

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Observation 2e049b6f-6709-49e6-b409-0272f1b066d4 · outbound

This paper cites Accelerated mirror descent in continuous and discrete time.Advances in Neural Information Processing Systems, 28, 2015.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Accelerated mirror descent in continuous and discrete time.Advances in Neural Information Processing Systems, 28, 2015

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.234856Z

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Observation cd1193eb-1ff4-478c-a2c6-9faa186d4a98 · outbound

This paper cites A convergent single-loop algorithm for relaxation of gromov-wasserstein in graph data.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods A convergent single-loop algorithm for relaxation of gromov-wasserstein in graph data

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.224089Z

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Observation 57366779-9df4-4c33-9722-d257500277aa · outbound

This paper cites Implicit bias of gradient descent on reparametrized models: On equivalence to mirror descent.Advances in Neural Information Processing Systems, 35:34626–34640, 2022.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Implicit bias of gradient descent on reparametrized models: On equivalence to mirror descent.Advances in Neural Information Processing Systems, 35:34626–34640, 2022

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.213251Z

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Observation 3b3f1406-6f6c-4a4c-aa3a-e98a7188cae9 · outbound

This paper cites Relatively smooth convex optimization by first-order methods, and applications.SIAM Journal on Optimization, 28(1):333–354, 2018.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Relatively smooth convex optimization by first-order methods, and applications.SIAM Journal on Optimization, 28(1):333–354, 2018

Reference 44

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This paper cites Pearson, 1999.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Pearson, 1999

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.194071Z

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Observation dd0fc6f4-3e09-4e87-b9b1-672c196bd54f · outbound

This paper cites Problem complexity and method efficiency in optimization.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Problem complexity and method efficiency in optimization

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.182447Z

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This paper cites Feature selection,L1 vs.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Feature selection,L1 vs

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.170772Z

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Observation f00b537c-52bd-45e0-874a-dc8cce7323eb · outbound

This paper cites On preparation theorems forran,exp-definable functions.Journal of Logic and Analysis, 15, 2023.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods On preparation theorems forran,exp-definable functions.Journal of Logic and Analysis, 15, 2023

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.159132Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1e3f14f3-bc1b-40e9-b5e1-d27689fc7c91 · outbound

This paper cites On the sequential convergence of Lloyd’s algorithms.Mathematics of Operations Research, 2025.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods On the sequential convergence of Lloyd’s algorithms.Mathematics of Operations Research, 2025

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.147749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d671da71-2205-4569-b9e2-7e7226ff39bd · outbound

This paper cites Springer Science & Business Media, Berlin, Heidelberg, 2009.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Springer Science & Business Media, Berlin, Heidelberg, 2009

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-08T11:35:12.731910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 106fc739-e41a-49e9-bef7-66f1729ca1a4 · outbound

This paper cites Princeton University Press, 2015.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Princeton University Press, 2015

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.130299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dae4e469-e314-4a6e-8095-5a91feac85a5 · outbound

This paper cites Generalized self-concordant functions: A recipe for newton-type methods.Mathematical Programming, 178:145 – 213, 2019.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Generalized self-concordant functions: A recipe for newton-type methods.Mathematical Programming, 178:145 – 213, 2019

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.118923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2b887cf9-1883-4ab7-a517-6b1e7f1da27a · outbound

This paper cites Approximate Bregman proximal gradient algo- rithm for relatively smooth nonconvex optimization.Computational Optimization and Applications, 90(1):227–256, 2025.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Approximate Bregman proximal gradient algo- rithm for relatively smooth nonconvex optimization.Computational Optimization and Applications, 90(1):227–256, 2025

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-08T11:35:12.742188Z

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Unavailable: canonical work link unavailable.

Observation 07b6b83a-8ff0-4d17-ad4e-9173c71deb0d · outbound

This paper cites New Bregman proximal type algorithms for solving DC optimization problems.Computational Optimization and Applications, 83(3):893–931, 2022.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods New Bregman proximal type algorithms for solving DC optimization problems.Computational Optimization and Applications, 83(3):893–931, 2022

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-08T11:35:12.745636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35638ac8-7275-4ac3-941a-d23dd4ca3154 · outbound

This paper cites A simplified view of first order methods for optimization.Mathematical Programming, Series B, 170(1):67–96, 2018.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods A simplified view of first order methods for optimization.Mathematical Programming, Series B, 170(1):67–96, 2018

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-08T11:35:12.748770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5358f00-5a4a-40f1-8525-b2312b4de3e3 · outbound

This paper cites A generalization of the Tarski-Seidenberg theorem, and some nondefinability results.American Mathematical Society, 15(2), 1986.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods A generalization of the Tarski-Seidenberg theorem, and some nondefinability results.American Mathematical Society, 15(2), 1986

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.088260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 79a1bdb5-0604-4a22-b556-1c1c494619e2 · outbound

This paper cites Cambridge University Press, 1998.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Cambridge University Press, 1998

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.076425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b2936186-9c46-47ba-bb03-524190489591 · outbound

This paper cites Geometric categories and o-minimal structures.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Geometric categories and o-minimal structures

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.065334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c7023ccc-bab1-4e6c-b99f-2bf8a6abfabb · outbound

This paper cites Linear convergence of a proximal alternating minimization method with extrapolation forℓ1-norm principal component analysis.SIAM Journal on Optimization, 33(2):684–712, 2023.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Linear convergence of a proximal alternating minimization method with extrapolation forℓ1-norm principal component analysis.SIAM Journal on Optimization, 33(2):684–712, 2023

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.053741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 685fe92a-cce0-4512-a821-3005a4b22ba4 · outbound

This paper cites Inertial proximal gradient methods with Bregman regularization for a class of nonconvex optimization problems.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Inertial proximal gradient methods with Bregman regularization for a class of nonconvex optimization problems

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-08T11:35:12.765722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33b8eb79-377c-47f5-8b09-aa508e8d3d9b · outbound

This paper cites Bregman proximal point algorithm revisited: A new inexact version and its inertial variant.SIAM Journal on Optimization, 32(3):1523–1554, 2022.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Bregman proximal point algorithm revisited: A new inexact version and its inertial variant.SIAM Journal on Optimization, 32(3):1523–1554, 2022

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.034957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3a7ff8ac-9f19-4643-91a6-8c6bf2e416fb · outbound

This paper cites Inexact Bregman proximal gradient method and its inertial variant with absolute and partial relative stopping criteria.Mathematics of Operations Research, 2025.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Inexact Bregman proximal gradient method and its inertial variant with absolute and partial relative stopping criteria.Mathematics of Operations Research, 2025

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:13.023031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2acdd954-fbee-4fe6-8528-2b420ca4ecf1 · outbound

This paper cites Proximal-like incremental aggregated gradient method with linear convergence under Bregman distance growth conditions.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Proximal-like incremental aggregated gradient method with linear convergence under Bregman distance growth conditions

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-08T11:35:12.776570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa11772e-2101-4601-aac1-6b03a7b2d27c · outbound

This paper cites Level-set subdifferential error bounds and linear convergence of Bregman proximal gradient method.Journal of Optimization Theory and Applications, 189(3):889–918, 2021.

A Unified Framework for Iterate Convergence of Bregman Proximal Methods Level-set subdifferential error bounds and linear convergence of Bregman proximal gradient method.Journal of Optimization Theory and Applications, 189(3):889–918, 2021

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T11:35:12.902270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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