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Paper Citation Record · LEDGER

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk

As of 10 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2606.11515.

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pith.paper-citation-record.v1
2606.11515 v1

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measured 66 of 66 reference resolution

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66 of 66 outbound references displayed

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Outbound references

Observation d6f977f4-a4ad-4f9c-9e7f-a3e081ccc4a2 · outbound

This paper cites Artzner, F.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Artzner, F

Reference 1

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Observation 735f297d-16a0-471a-a8f5-b1bf79cba0e2 · outbound

This paper cites Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling.Monte Carlo Methods and Applications, 15(3):173–210, 2009.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling.Monte Carlo Methods and Applications, 15(3):173–210, 2009

Reference 2

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Observation 6224d1d8-012d-423d-8bf1-0e146bff64d3 · outbound

This paper cites Adaptive sampling strategies for risk-averse stochastic optimization with constraints.IMA Journal of Numerical Analysis, 43(6):3729–3765, 2023.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Adaptive sampling strategies for risk-averse stochastic optimization with constraints.IMA Journal of Numerical Analysis, 43(6):3729–3765, 2023

Reference 3

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Observation 07621c4d-b393-49ac-bdb2-edab278eb73c · outbound

This paper cites Bertsekas.Nonlinear Programming.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Bertsekas.Nonlinear Programming

Reference 4

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Observation edf273b1-0e61-40cb-8074-b7d23e9bb0d6 · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 5

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Observation b40d27cb-5c91-4c5e-80d6-71bea355c42d · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 6

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Observation 9786183b-5130-45db-9c85-1ae18b1248ba · outbound

This paper cites Maximum Block Improvement and Polynomial Optimization.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Maximum Block Improvement and Polynomial Optimization

Reference 7

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Observation 4a08d056-1cbf-4d5d-a79e-52cba00b603b · outbound

This paper cites Chen and M.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Chen and M

Reference 8

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Observation 8ea055e9-923c-4ec6-a106-1ef67424e94a · outbound

This paper cites Csisz´ ar.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Csisz´ ar

Reference 9

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Observation 75cdbefb-b28d-4a46-98aa-feee2ed87450 · outbound

This paper cites Csisz´ ar.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Csisz´ ar

Reference 10

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Observation 86e04698-ed72-439a-b490-babe7df9cbe9 · outbound

This paper cites Csisz´ ar.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Csisz´ ar

Reference 11

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Observation 4755d45c-0821-415e-acfa-92a9c86299be · outbound

This paper cites Csisz´ ar and F.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Csisz´ ar and F

Reference 12

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Observation 9f7fb1d1-6c59-44ae-975d-774d8a23045f · outbound

This paper cites Csisz´ ar and F.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Csisz´ ar and F

Reference 13

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Observation 235188a6-4b0a-4b40-8d29-d7db9c8bf8f6 · outbound

This paper cites Danskin.The Theory of Max-Min and Its Application to Weapons Allocation Problems, volume 5 ofEconometrics and Operations Research.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Danskin.The Theory of Max-Min and Its Application to Weapons Allocation Problems, volume 5 ofEconometrics and Operations Research

Reference 14

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Observation 46d01c66-e843-4300-8b23-d4a71a165b6c · outbound

This paper cites Efficient black-box importance sampling for VaR and CVaR estimation.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Efficient black-box importance sampling for VaR and CVaR estimation

Reference 15

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:313db1a4c2a58c599da28a7c3c1384e5af12f8581409cca1d47e035fcd3fd48d

Observation 65205852-f8ca-4c80-9ba0-2fb724c03dc3 · outbound

This paper cites Approximate Iterations in Bregman-Function-Based Proximal Algorithms.Mathematical program- ming, 83(1):113–123, 1998.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Approximate Iterations in Bregman-Function-Based Proximal Algorithms.Mathematical program- ming, 83(1):113–123, 1998

Reference 16

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Observation 876eb6bc-b0b7-415c-8580-b360e17b20da · outbound

This paper cites Grechuk, A.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Grechuk, A

Reference 17

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Observation 5065b3b8-81de-4202-96e0-90e3ce569756 · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 18

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Observation 44844b5d-8f77-4cc7-b63f-caadb29eb72d · outbound

This paper cites Risk-averse design of tall buildings for uncertain wind conditions.Computer Methods in Applied Mechanics and Engineering, 402:115371, 2022.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Risk-averse design of tall buildings for uncertain wind conditions.Computer Methods in Applied Mechanics and Engineering, 402:115371, 2022

Reference 19

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Observation 472e2082-f3fb-4696-b2ad-5f30571076df · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 20

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Observation 863e5f5c-2490-4351-afd8-b5d64eb97ae2 · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 21

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Observation 7dd11c2e-6f68-44fe-82b3-c2fa22cbe5d9 · outbound

This paper cites All Roads Lead to Rome: Path-Following Augmented Lagrangian Methods via Bregman Proximal Regularization.arXiv preprint arXiv.2602.15710, 2026.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk All Roads Lead to Rome: Path-Following Augmented Lagrangian Methods via Bregman Proximal Regularization.arXiv preprint arXiv.2602.15710, 2026

Reference 22

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Observation b3acfb5e-d776-4eff-be95-189f3c46507d · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 23

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Observation 1ba2a2aa-1393-46a0-8001-fd62b44d351f · outbound

This paper cites On the Convergence of the Coordinate Descent Method for Convex Differentiable Mini- mization.Journal of Optimization Theory and Applications, 72(1):7–35, 1992.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk On the Convergence of the Coordinate Descent Method for Convex Differentiable Mini- mization.Journal of Optimization Theory and Applications, 72(1):7–35, 1992

Reference 24

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Observation 1ba67e0f-3b71-4ede-be2e-5bd6a7cecc95 · outbound

This paper cites Adaptive Gradient Descent without Descent.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Adaptive Gradient Descent without Descent

Reference 25

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Observation 04bc6d6f-a259-44a4-993b-c29d97014dc5 · outbound

This paper cites Adaptive Proximal Gradient Method for Convex Optimization.Advances in Neural Information Processing Systems, 37:100670–100697, 2024.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Adaptive Proximal Gradient Method for Convex Optimization.Advances in Neural Information Processing Systems, 37:100670–100697, 2024

Reference 26

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Observation d95fbc34-22ba-4262-bd0b-5069dd070e5f · outbound

This paper cites Martinet.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Martinet

Reference 27

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Observation 688e13c0-8e38-4e78-ae05-92c2cf31c606 · outbound

This paper cites CVaR Portfolio Optimization.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk CVaR Portfolio Optimization

Reference 28

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Observation 2177fe1b-560a-4623-8687-1b16caf9f8a5 · outbound

This paper cites Mirzoakhmedov and S.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Mirzoakhmedov and S

Reference 29

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Observation 37aa8120-3cf4-4fde-a220-11a164537cca · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 30

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Observation f580eb63-3fe6-4dac-8654-1ad5e0223359 · outbound

This paper cites Nemirovski and D.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Nemirovski and D

Reference 31

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Observation 0954a986-146b-4d4a-a557-768d3b367084 · outbound

This paper cites Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems.SIAM Journal on Optimization, 22(2):341–362, 2012.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems.SIAM Journal on Optimization, 22(2):341–362, 2012

Reference 32

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Observation fc932e2c-ec0a-43d5-af19-3e60572e0627 · outbound

This paper cites Springer, 2018.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Springer, 2018

Reference 33

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Observation 3137819c-7a75-47ab-851b-1c1f6d1cec9f · outbound

This paper cites Efficient Random Coordinate Descent Algorithms for Large-Scale Structured Nonconvex Optimization.Journal of Global Optimization, 61(1):19–46, 2015.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Efficient Random Coordinate Descent Algorithms for Large-Scale Structured Nonconvex Optimization.Journal of Global Optimization, 61(1):19–46, 2015

Reference 34

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Observation 78f8f2ee-939b-4830-b388-d2e6e1bc06e6 · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 35

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Observation cf7d16e3-02a0-4d60-b48f-bde5b4dac604 · outbound

This paper cites An adaptive importance sampling algorithm for risk-averse optimization.Journal of Computational Physics, 547:114548, 2026.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk An adaptive importance sampling algorithm for risk-averse optimization.Journal of Computational Physics, 547:114548, 2026

Reference 36

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Observation ab120d37-e4c4-4ac3-ad85-efc53b9bfe38 · outbound

This paper cites Pinsker.Information and Information Stability of Random Variables and Processes.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Pinsker.Information and Information Stability of Random Variables and Processes

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Observation 47d673b4-7e26-430b-a470-7693203326ee · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

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Observation ca3ae330-126d-4058-b8f4-d63506e02c10 · outbound

This paper cites Portfolio Safeguard Help Manual, 2026.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Portfolio Safeguard Help Manual, 2026

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Observation e51ea9dc-af1c-4bfd-ad8f-40a99bb794c6 · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:8068377a8556522ca4248d7f2357b43be1c5ab267f26295ca260d9a356189352

Observation 4a1f2559-7ccd-4146-a39b-24e184c3f4a7 · outbound

This paper cites Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function.Mathematical Programming, 144(1–2):1–38, 2014.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function.Mathematical Programming, 144(1–2):1–38, 2014

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:ba23847648d024465fae0f3a120475379964cef4f5424d6bfc8551f117693efc

Observation 79607a04-53b0-4a43-bff0-cb2022c69c07 · outbound

This paper cites On Optimal Probabilities in Stochastic Coordinate Descent Methods.Optimization Letters, 10(6):1233–1243, 2016.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk On Optimal Probabilities in Stochastic Coordinate Descent Methods.Optimization Letters, 10(6):1233–1243, 2016

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:c015115bfdd97f38f0b230975dbd5ac15510d2b69233fe3e0cd7ef619281d6ac

Observation 218e4472-788f-4c2d-8442-795af6ba55bf · outbound

This paper cites Robbins and S.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Robbins and S

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:92e56753f0bfdfc13a598a2ed38118fdef88844e97510177b3687491e94b1770

Observation 85732f89-08f8-4a2e-96d5-b7585bfcb905 · outbound

This paper cites A Convergence Theorem for Nonnegative Almost Supermartingales and Some Applications.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk A Convergence Theorem for Nonnegative Almost Supermartingales and Some Applications

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Observation 607d1294-35bd-4ad8-8a9b-ed9ca05803b6 · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 45

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:e0eda075da4ed81892599998940050186fce892af421f7dcafe94df6e900b105

Observation cbe20a93-20ab-4af4-bffe-fcb1d954818d · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 46

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:062e62566ff9e6b2dda59030c122f93e46d56e5351788667587e52d79394be71

Observation 59cae1a6-e2e3-46ce-b1fa-3d0b3e9ce27a · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 47

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:d3ebbd8a1d831b680c1c5483ef14cf04aab509c478be546d753aab832d5f9d69

Observation 68689158-920a-44c8-b821-6f7d73b3f946 · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 48

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:1c01837844f2a5e3299bca780e79cfe426fb6162e185a07a2a0e80507c1870a3

Observation 987cdc63-e6fb-4daa-ac32-f2f37b14266b · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 49

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:be7a63201f8b92e06decc7b97572b99de834cc6a4d0c0268115760983949120f

Observation e48b6615-8cf0-49ab-b2f0-1b863e49daba · outbound

This paper cites Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Augmented Lagrangians and Applications of the Proximal Point Algorithm in Convex Programming

Reference 50

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Observation 846ebb3d-4af1-48af-90b6-7d970e79f97b · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 51

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:87cc8f48a1019e406956c20c43f2549850ac05a37c8b173ce127be14c6673675

Observation 8ae5fb94-193b-4e86-bd71-de3f9c5a473b · outbound

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Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 52

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Observation 96f18851-8b5c-4d71-b5b5-03755f367f61 · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 53

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:8109dab0f9685f2de6b2fb5eb08dc6d6584d482b808e8c7978587db0b6012c7d

Observation ccdb8b48-c3d9-4e13-b76b-f024748af1c2 · outbound

This paper cites Stochastic Methods forℓ 1 Regularized Loss Minimization.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Stochastic Methods forℓ 1 Regularized Loss Minimization

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Observation 5d732574-d430-4b28-a832-d5b01ef5673b · outbound

This paper cites Stochastic Methods forℓ 1 Regularized Loss Minimization.Journal of Machine Learning Research, 12(52):1865–1892, 2011.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Stochastic Methods forℓ 1 Regularized Loss Minimization.Journal of Machine Learning Research, 12(52):1865–1892, 2011

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Observation fc038c16-488f-4a67-a867-61d04da56dfd · outbound

This paper cites Shor.Nondifferentiable Optimization and Polynomial Problems, volume 24 ofNonconvex Optimization and Its Applications.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Shor.Nondifferentiable Optimization and Polynomial Problems, volume 24 ofNonconvex Optimization and Its Applications

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Observation 75d4df9b-595f-45e9-a4ca-79be55ea255f · outbound

This paper cites An Inexact Hybrid Generalized Proximal Point Algorithm and Some New Results on the Theory of Bregman Functions.Mathematics of Operations Research, 25(2):214–230, 2000.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk An Inexact Hybrid Generalized Proximal Point Algorithm and Some New Results on the Theory of Bregman Functions.Mathematics of Operations Research, 25(2):214–230, 2000

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Observation 9e47f577-f438-4381-ab8f-5b5c825d21e4 · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

Reference 58

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:b9af459a4effcd12f404948d486cfee19fbd97c0f9280a7d52044239306c0182

Observation c8ea998c-73ac-4976-ba8c-5c254b36ac76 · outbound

This paper cites InProceed- ings of the 25th International Conference on Machine Learning, ICML ’08, page 1056–1063, New York, NY, USA,.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk InProceed- ings of the 25th International Conference on Machine Learning, ICML ’08, page 1056–1063, New York, NY, USA,

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:f046ebdbc964f6b28de32e5c45d09acbf6bcdfe4ee92e09a833ec5c217185eaf

Observation b56178f0-26fa-41e0-9d68-0fd4adc9b3fd · outbound

This paper cites an unresolved cited work.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Unresolved cited work

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:c5e8f111214905afb54f09606eb3e2df2e874463f1c106c96080fd3be01c466b

Observation 7a08018b-971c-485a-a012-55b2103ef1e6 · outbound

This paper cites Optimizing the CVaR via sampling.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Optimizing the CVaR via sampling

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:ef18849dcd457a6b53126bfc98f59f64f5a8e580552e58b4fc2fb7d3d6f9a91e

Observation 15fb9fce-80a8-4046-9bf1-6f41055253f2 · outbound

This paper cites Teboulle.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Teboulle

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:3b6ca6bf5b326fe300d0ae0b90e60480260f6243c49fa63f76a865766ece7f07

Observation 71f78544-377a-4fa5-93ff-f80938db31b3 · outbound

This paper cites Dual Ascent Methods for Problems with Strictly Convex Costs and Linear Constraints: A Unified Approach.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Dual Ascent Methods for Problems with Strictly Convex Costs and Linear Constraints: A Unified Approach

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:59701546c53badbef4ee20f87f74b5a91b40fe6722b256974bb328d5e740136b

Observation af0112da-2280-438c-a671-b9dbf11d8848 · outbound

This paper cites Tsybakov.Introduction to Nonparametric Estimation.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Tsybakov.Introduction to Nonparametric Estimation

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:b25e9c83d2d08df468c1a604084f104f9da44a468f928adb9ea58afc3041cb87

Observation 1a6b1e80-3c09-4906-9b1c-0790f353e123 · outbound

This paper cites Solving Large-Scale Linear Prediction Problems Using Stochastic Gradient Descent Algorithms.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Solving Large-Scale Linear Prediction Problems Using Stochastic Gradient Descent Algorithms

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source=pdf_text observed=2026-06-27T11:57:40.571364Z digest=sha256:3f6e80013efbcee735506dd5f0d1b81d003e4443c7c059ac2d37eaf7b6ceaf38

Observation 59cdca1c-5bf9-4e57-b281-0e7273425e51 · outbound

This paper cites Stochastic Primal–Dual Coordinate Method for Regularized Empirical Risk Minimization.

Exponential Adaptive Smoothing and Importance Sampling for Optimization of the Conditional Value-at-Risk Stochastic Primal–Dual Coordinate Method for Regularized Empirical Risk Minimization

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