Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition | Paper Citation Record

Observation f5b51b0b-44fe-4752-99ca-2b2fdbdf41c6 · outbound

This paper cites Deep learning with differential privacy.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Deep learning with differential privacy

Reference 1

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Observation e819a4fa-e76d-4ed6-94cc-547c0c39ba41 · outbound

This paper cites Differentially private assouad, fano, and le cam.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private assouad, fano, and le cam

Reference 2

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Observation 7605ccf0-b105-42b7-b7ae-30dd3a57fe4b · outbound

This paper cites Private adaptive gradient methods for convex optimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private adaptive gradient methods for convex optimization

Reference 3

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Observation 6cc6b33a-46ec-40d6-ae07-3b17ea4e30a9 · outbound

This paper cites Adapting to function difficulty and growth conditions in private optimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Adapting to function difficulty and growth conditions in private optimization

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:12.267610Z

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Observation 8dc47ccb-f724-440d-96e1-71096c608fa4 · outbound

This paper cites Private stochastic convex optimization with heavy tails: Near-optimality from simple reductions.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private stochastic convex optimization with heavy tails: Near-optimality from simple reductions

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:12.038894Z

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Observation a1afcc1d-bec8-41bc-a27e-46ef5b0409b9 · outbound

This paper cites Privacy and Statistical Risk: Formalisms and Minimax Bounds.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Privacy and Statistical Risk: Formalisms and Minimax Bounds

Reference 6

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Observation c2ce5d31-4a52-485f-968e-1a68c42abfad · outbound

This paper cites Private empirical risk minimization: Efficient algorithms and tight error bounds.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private empirical risk minimization: Efficient algorithms and tight error bounds

Reference 7

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Observation ffc5892d-4e66-427c-b576-56a9395e114e · outbound

This paper cites Private Stochastic Convex Optimization with Optimal Rates.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private Stochastic Convex Optimization with Optimal Rates

Reference 8

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Observation 8d34f187-6b6f-415a-9410-af80b8e85c4f · outbound

This paper cites Statistical advances in the biomedical science.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Statistical advances in the biomedical science

Reference 9

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Observation b8ae2518-6d0f-4cc3-9ccc-757e5b1eea4d · outbound

This paper cites A method for finding projections onto the intersection of convex sets in hilbert spaces.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition A method for finding projections onto the intersection of convex sets in hilbert spaces

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:11.124383Z

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Observation 39b436ce-1d21-40e9-b24c-0fe69a302e8a · outbound

This paper cites Propose, Test, Release: Differentially private estimation with high probability.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Propose, Test, Release: Differentially private estimation with high probability

Reference 11

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Observation 5276250d-bfe5-4e1d-97cb-a935a81bfe3f · outbound

This paper cites Concentrated differential privacy: Simplifications, extensions, and lower bounds.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Concentrated differential privacy: Simplifications, extensions, and lower bounds

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:10.804248Z

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Observation 39a9f412-ffe4-4e74-8c20-b443433b7013 · outbound

This paper cites Differentially private empirical risk minimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private empirical risk minimization

Reference 13

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Observation 370fb437-e22f-45da-9eff-45f948acc959 · outbound

This paper cites Quantizing heavy-tailed data in statistical estimation:(near) minimax rates, covariate quantization, and uniform recovery.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Quantizing heavy-tailed data in statistical estimation:(near) minimax rates, covariate quantization, and uniform recovery

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:10.482281Z

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Observation 678dcfa1-56c1-477c-8673-7aa0bb6ea7d7 · outbound

This paper cites Revisiting differentially private relu regression.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Revisiting differentially private relu regression

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:10.115799Z

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Observation ac88e871-ec3f-4b99-bfa4-e74a6d66aaf5 · outbound

This paper cites Nearly optimal differentially private relu regression.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Nearly optimal differentially private relu regression

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:09.843080Z

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Observation 81eb4345-0ed9-4d52-8190-7d25d4c8ba9e · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Calibrating noise to sensitivity in private data analysis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:09.513747Z

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Observation 03faef9c-93db-4b44-a266-83a6286ece0e · outbound

This paper cites An algorithm for restricted least squares regression.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition An algorithm for restricted least squares regression

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:09.264757Z

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Observation 0b85ac43-45a5-44ff-9b81-1f7f9c9a5425 · outbound

This paper cites High probability generalization bounds for uniformly stable algorithms with nearly optimal rate.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition High probability generalization bounds for uniformly stable algorithms with nearly optimal rate

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:08.894748Z

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Observation df8a2c65-a7a0-42a8-8644-b41bc357d84a · outbound

This paper cites Private stochastic convex optimization: optimal rates in linear time.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private stochastic convex optimization: optimal rates in linear time

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:08.659128Z

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Observation c904bd72-8712-4326-8e39-b83303c75fc2 · outbound

This paper cites Hiding among the clones: A simple and nearly optimal analysis of privacy amplification by shuffling.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Hiding among the clones: A simple and nearly optimal analysis of privacy amplification by shuffling

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:08.416000Z

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Observation 915791e3-9ba0-42ce-881b-8683d4b2233d · outbound

This paper cites Train faster, generalize better: Stability of stochastic gradient descent.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Train faster, generalize better: Stability of stochastic gradient descent

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:08.154747Z

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Observation 5064ad7d-0c1d-4a00-8b7c-0c8b62cc9035 · outbound

This paper cites High dimensional differentially private stochastic optimization with heavy-tailed data.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition High dimensional differentially private stochastic optimization with heavy-tailed data

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:07.825751Z

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Observation 19d075c1-1f51-4ece-9b82-c980f1625946 · outbound

This paper cites Pairwise learning with differential privacy guarantees.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Pairwise learning with differential privacy guarantees

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:07.654838Z

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Observation fbf1bd5e-f442-4e85-ac35-4e56fde5cb5a · outbound

This paper cites Heavy-tailed distributions and robustness in economics and finance, volume 214.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Heavy-tailed distributions and robustness in economics and finance, volume 214

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:07.364836Z

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Observation 2a65e795-cc34-4d55-a9bf-fe444e73af38 · outbound

This paper cites Private mean estimation of heavy-tailed distributions.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private mean estimation of heavy-tailed distributions

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:07.106243Z

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Observation e10d8172-ac3b-478a-8a77-f05b1c7df2d8 · outbound

This paper cites Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-05T06:03:57.000646Z

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Observation d7ace8a1-6dd8-48e3-9c8d-da8d92f96342 · outbound

This paper cites Improved rates for differentially private stochastic convex optimization with heavy-tailed data.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Improved rates for differentially private stochastic convex optimization with heavy-tailed data

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:06.765504Z

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Observation eb12841a-7dd8-4f0a-b3b9-99dc44261d35 · outbound

This paper cites Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:06.426471Z

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Observation 28fb8aad-4028-4114-a135-78605cf1cca0 · outbound

This paper cites Efficient private empirical risk minimization for high-dimensional learning.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Efficient private empirical risk minimization for high-dimensional learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:06.078584Z

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Observation 712a3ba2-7960-4e4a-bec4-5f6680995fae · outbound

This paper cites Private convex empirical risk minimization and high-dimensional regression.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private convex empirical risk minimization and high-dimensional regression

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:05.845030Z

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Observation d8792616-a54f-444e-861d-2035ddd86d64 · outbound

This paper cites Fast rates for exp-concave empirical risk minimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Fast rates for exp-concave empirical risk minimization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:05.538006Z

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Observation c3956056-6b48-4d9f-a97f-3a93868978d4 · outbound

This paper cites Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Fast Rates of ERM and Stochastic Approximation: Adaptive to Error Bound Conditions

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-05T06:03:56.714100Z

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Observation 798e9e8d-ae27-490f-8fa8-436745272eee · outbound

This paper cites Robust and Differentially Private Mean Estimation.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Robust and Differentially Private Mean Estimation

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-05T06:03:56.408995Z

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Observation 6283abe3-b35e-4c7d-869b-b21910e739d4 · outbound

This paper cites Private stochastic optimization with large worst-case lipschitz parameter: Optimal rates for (non-smooth) convex losses and extension to non-convex losses.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private stochastic optimization with large worst-case lipschitz parameter: Optimal rates for (non-smooth) convex losses and extension to non-convex losses

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:05.224235Z

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Observation 9713e4b7-b1d9-4510-8b98-b7c0940a2771 · outbound

This paper cites Privacy integrated queries: an extensible platform for privacy-preserving data analysis.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Privacy integrated queries: an extensible platform for privacy-preserving data analysis

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:04.884087Z

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Observation dbe9d191-ce08-46a7-9959-0869070e5985 · outbound

This paper cites Optimal rates for first-order stochastic convex optimization under Tsybakov noise condition.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Optimal rates for first-order stochastic convex optimization under Tsybakov noise condition

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-05T06:03:56.150376Z

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Observation 8f90b9ed-7d05-4965-b58a-9d732c0d7ee3 · outbound

This paper cites Algorithmic connections between active learning and stochastic convex optimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Algorithmic connections between active learning and stochastic convex optimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:04.610716Z

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Observation 43831581-8bf7-44cb-8cad-05abfa5b92c9 · outbound

This paper cites Is interaction necessary for distributed private learning? In 2017 IEEE Symposium on Security and Privacy (SP), pp.\ 58--77.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Is interaction necessary for distributed private learning? In 2017 IEEE Symposium on Security and Privacy (SP), pp.\ 58--77

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:04.314743Z

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Observation 89466734-2a05-4c96-9126-4ab705569812 · outbound

This paper cites Faster rates of private stochastic convex optimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Faster rates of private stochastic convex optimization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:03.995851Z

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Observation f8add3e9-1254-446b-90c3-7f9f01276d71 · outbound

This paper cites Differentially private stochastic convex optimization in (non)-euclidean space revisited.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private stochastic convex optimization in (non)-euclidean space revisited

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:03.722968Z

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Observation d4e1f629-f516-47ff-abe0-89738c8f5c63 · outbound

This paper cites Faster rates of differentially private stochastic convex optimization.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Faster rates of differentially private stochastic convex optimization

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:03.417125Z

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Observation 5671799f-f6b6-477f-88ea-aca026363b15 · outbound

This paper cites Private stochastic convex optimization and sparse learning with heavy-tailed data revisited.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private stochastic convex optimization and sparse learning with heavy-tailed data revisited

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:03.094742Z

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Observation b8cbc73c-cb15-4d6f-bff1-bb4ca7bc8fe2 · outbound

This paper cites Optimal rates of (locally) differentially private heavy-tailed multi-armed bandits.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Optimal rates of (locally) differentially private heavy-tailed multi-armed bandits

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:02.777956Z

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Observation c3143b29-2dcd-4713-9d6e-19fc7ed87db5 · outbound

This paper cites Differentially Private Sparse Linear Regression with Heavy-tailed Responses.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially Private Sparse Linear Regression with Heavy-tailed Responses

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-05T06:03:55.887247Z

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Observation 3bd38622-6120-40f8-8b5f-573e16187d78 · outbound

This paper cites Fast rates in statistical and online learning.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Fast rates in statistical and online learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:02.364755Z

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Observation efa9d90e-c418-4787-98e3-e93caeba394a · outbound

This paper cites Differentially private _1 -norm linear regression with heavy-tailed data.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private _1 -norm linear regression with heavy-tailed data

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:02.014936Z

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Observation eb614c0f-6a73-4a79-aff3-be6958ded636 · outbound

This paper cites Private least absolute deviations with heavy-tailed data.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Private least absolute deviations with heavy-tailed data

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:01.634749Z

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Observation 11ef6f1e-313c-4d7b-9e61-110f58f568d4 · outbound

This paper cites Differentially private empirical risk minimization revisited: Faster and more general.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private empirical risk minimization revisited: Faster and more general

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:01.363145Z

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Observation 372b8de9-fa69-4179-a882-1a6b304d08de · outbound

This paper cites Empirical risk minimization in non-interactive local differential privacy revisited.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Empirical risk minimization in non-interactive local differential privacy revisited

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:00.974171Z

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Observation 902933e3-3507-43ef-8e81-3e3384f49950 · outbound

This paper cites Differentially private empirical risk minimization with non-convex loss functions.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private empirical risk minimization with non-convex loss functions

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:00.425168Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 425eec13-0ae7-4ad0-9ab4-739401c89ecf · outbound

This paper cites Noninteractive locally private learning of linear models via polynomial approximations.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Noninteractive locally private learning of linear models via polynomial approximations

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:04:00.115955Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ede49832-255d-47b6-976d-59346775c3b6 · outbound

This paper cites On differentially private stochastic convex optimization with heavy-tailed data.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition On differentially private stochastic convex optimization with heavy-tailed data

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:59.727517Z

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Observation 6e353a7a-070d-4da7-86ed-0e17b8eff04d · outbound

This paper cites Statistical methods for the analysis of biomedical data, volume 371.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Statistical methods for the analysis of biomedical data, volume 371

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:59.385288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cf67538d-e93b-4980-981f-8656005c9690 · outbound

This paper cites Bolt-on differential privacy for scalable stochastic gradient descent-based analytics.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Bolt-on differential privacy for scalable stochastic gradient descent-based analytics

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:58.984748Z

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Observation e9bd223e-24c4-4f07-8349-3967dc3ac2da · outbound

This paper cites Differentially private episodic reinforcement learning with heavy-tailed rewards.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private episodic reinforcement learning with heavy-tailed rewards

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:58.718077Z

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Observation 8d32a784-e39a-404a-a6b2-669b75a08c88 · outbound

This paper cites On private and robust bandits.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition On private and robust bandits

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:58.399488Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 46466ba9-6cb4-4f87-b292-5200975563ea · outbound

This paper cites Stochastic convex optimization: Faster local growth implies faster global convergence.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Stochastic convex optimization: Faster local growth implies faster global convergence

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:58.113061Z

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Observation 09562325-e18b-4f82-9fb7-8cbc50d5a620 · outbound

This paper cites Differentially private pairwise learning revisited.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition Differentially private pairwise learning revisited

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:57.805830Z

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Observation d502aa98-5b3e-4c6e-9509-dae8e4b478fe · outbound

This paper cites A simple analysis for exp-concave empirical minimization with arbitrary convex regularizer.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition A simple analysis for exp-concave empirical minimization with arbitrary convex regularizer

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T06:03:57.456418Z

Source-reported events for the cited work

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Observation 6fc91eaf-d742-4e7d-9e35-b4429f217f23 · outbound

This paper cites write newline.

Beyond Ordinary Lipschitz Constraints: Differentially Private Stochastic Optimization with Tsybakov Noise Condition write newline

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T06:03:55.593835Z

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