Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise | Paper Citation Record

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This paper cites A survey on distributed machine learning.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise A survey on distributed machine learning

Reference 1

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This paper cites Modern robotics: Mechanics, planning, and control.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Modern robotics: Mechanics, planning, and control

Reference 2

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This paper cites Delay effects on consensus- based distributed economic dispatch algorithm in microgrid.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Delay effects on consensus- based distributed economic dispatch algorithm in microgrid

Reference 3

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This paper cites A survey of distributed optimization.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise A survey of distributed optimization

Reference 4

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This paper cites Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Machine learning at the wireless edge: Distributed stochastic gradient descent over-the-air

Reference 5

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Observation f59309f4-d466-4f84-a224-a2ef5b8a97c2 · outbound

This paper cites Convergence analysis of distributed stochastic gradient descent with shuffling.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Convergence analysis of distributed stochastic gradient descent with shuffling

Reference 6

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Observation fd1b7c86-f947-4d1b-89a5-efa003daf99c · outbound

This paper cites Distributed stochastic optimization and learning.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed stochastic optimization and learning

Reference 7

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Observation c974c6aa-2dd8-425f-9a2a-3030003d4f7a · outbound

This paper cites Distributed stochastic gradient descent with event-triggered communication.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed stochastic gradient descent with event-triggered communication

Reference 8

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Observation 851df9e2-7514-4a42-bc7f-27430c523dd2 · outbound

This paper cites Distributed stochastic gradient descent: Nonconvexity, nonsmoothness, and convergence to local minima.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed stochastic gradient descent: Nonconvexity, nonsmoothness, and convergence to local minima

Reference 9

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This paper cites A sharp estimate on the transient time of distributed stochastic 10 gradient descent.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise A sharp estimate on the transient time of distributed stochastic 10 gradient descent

Reference 10

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This paper cites Distributed learning in wireless networks: Recent progress and future challenges.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed learning in wireless networks: Recent progress and future challenges

Reference 11

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Observation ba47daf3-8d58-426d-b499-a721fca5b123 · outbound

This paper cites On the linear speedup analysis of communication efficient momentum sgd for distributed non-convex optimization.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise On the linear speedup analysis of communication efficient momentum sgd for distributed non-convex optimization

Reference 12

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Observation f5e6395e-6170-417c-a4b8-694516b1c578 · outbound

This paper cites Attention is all you need.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Attention is all you need

Reference 13

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This paper cites A primal-dual sgd algorithm for distributed nonconvex optimization.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise A primal-dual sgd algorithm for distributed nonconvex optimization

Reference 14

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This paper cites Stochastic gradient push for distributed deep learning.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Stochastic gradient push for distributed deep learning

Reference 15

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Observation 6eae199b-5fbd-4fbe-a669-7e6dd804d632 · outbound

This paper cites Distributed stochastic subgradient projection algorithms for convex optimization.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed stochastic subgradient projection algorithms for convex optimization

Reference 16

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Observation ef9d813e-bfb3-40a4-ab89-3cbad93ddc55 · outbound

This paper cites The heavy-tail phenomenon in sgd.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise The heavy-tail phenomenon in sgd

Reference 17

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Observation a8b48a10-f39e-44fa-9f34-58d73f8280c5 · outbound

This paper cites High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise

Reference 18

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Observation f9847547-0f16-4e24-8870-9fc940bcbceb · outbound

This paper cites On proximal policy optimization’s heavy-tailed gradients.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise On proximal policy optimization’s heavy-tailed gradients

Reference 19

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Observation 18480e0e-ec2d-48a0-9237-c63efcba3bb5 · outbound

This paper cites Revisiting the noise model of stochastic gradient descent.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Revisiting the noise model of stochastic gradient descent

Reference 20

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This paper cites Heavy-tail phenomenon in decentralized sgd.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Heavy-tail phenomenon in decentralized sgd

Reference 21

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This paper cites Why are adaptive methods good for attention models? Advances in Neural Information Processing Systems, 33:15383–15393, 2020.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Why are adaptive methods good for attention models? Advances in Neural Information Processing Systems, 33:15383–15393, 2020

Reference 22

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This paper cites BEiT: BERT Pre-Training of Image Transformers.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise BEiT: BERT Pre-Training of Image Transformers

Reference 23

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Observation ebb0db7c-a7ae-4ef3-bcf3-8370cbf8a9b4 · outbound

This paper cites High probability guarantees for nonconvex stochastic gradient descent with heavy tails.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise High probability guarantees for nonconvex stochastic gradient descent with heavy tails

Reference 24

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This paper cites heavier-tailed.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise heavier-tailed

Reference 25

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This paper cites A communication-efficient distributed gradient clipping algorithm for training deep neural networks.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise A communication-efficient distributed gradient clipping algorithm for training deep neural networks

Reference 26

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This paper cites Stochastic model- based minimization of weakly convex functions.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Stochastic model- based minimization of weakly convex functions

Reference 27

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This paper cites Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Solving (most) of a set of quadratic equalities: Composite optimization for robust phase retrieval

Reference 28

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This paper cites First-order convergence theory for weakly-convex-weakly- concave min-max problems.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise First-order convergence theory for weakly-convex-weakly- concave min-max problems

Reference 29

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This paper cites Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation

Reference 30

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This paper cites Delayed algorithms for distributed stochastic weakly convex optimization.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Delayed algorithms for distributed stochastic weakly convex optimization

Reference 31

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This paper cites On distributed nonconvex optimization: Projected subgradient method for weakly convex problems in networks.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise On distributed nonconvex optimization: Projected subgradient method for weakly convex problems in networks

Reference 32

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Observation 8390fcc0-bc37-4698-984c-da7767dba142 · outbound

This paper cites Distributed Stochastic Optimization under Heavy-Tailed Noises.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed Stochastic Optimization under Heavy-Tailed Noises

Reference 33

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This paper cites Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Online Distributed Optimization with Clipped Stochastic Gradients: High Probability Bound of Regrets

Reference 34

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This paper cites High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise

Reference 35

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This paper cites Convex analysis.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Convex analysis

Reference 36

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This paper cites Efficiency of minimizing compositions of convex functions and smooth maps.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Efficiency of minimizing compositions of convex functions and smooth maps

Reference 37

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This paper cites Distributed stochastic optimization with gradient tracking over strongly-connected networks.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed stochastic optimization with gradient tracking over strongly-connected networks

Reference 38

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This paper cites Distributed subgradient methods for multi-agent optimization.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed subgradient methods for multi-agent optimization

Reference 39

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This paper cites Distributed smooth convex optimization with coupled constraints.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Distributed smooth convex optimization with coupled constraints

Reference 40

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This paper cites Variational analysis, volume 317.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Variational analysis, volume 317

Reference 41

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This paper cites The nonsmooth landscape of phase retrieval.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise The nonsmooth landscape of phase retrieval

Reference 42

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This paper cites Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Gradient descent with random initialization: Fast global convergence for nonconvex phase retrieval

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:44:21.707491Z

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This paper cites Gradient-based learning applied to document recognition.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Gradient-based learning applied to document recognition

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:44:21.694897Z

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Observation 5aed5de4-78fc-4318-aeed-bd34be52e2cd · outbound

This paper cites Heavy- tailed distributions in combinatorial search.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Heavy- tailed distributions in combinatorial search

Reference 45

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This paper cites Proximal algorithms.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Proximal algorithms

Reference 46

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This paper cites Convergence rate analysis of distributed optimization with projected subgradient algorithm.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Convergence rate analysis of distributed optimization with projected subgradient algorithm

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:44:21.656332Z

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Observation 592a5798-0c7f-43e8-823d-5a0fa7899222 · outbound

This paper cites Constrained consensus and optimization in multi-agent networks.

Distributed Stochastic Optimization for Non-Smooth and Weakly Convex Problems under Heavy-Tailed Noise Constrained consensus and optimization in multi-agent networks

Reference 48

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