ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning | Paper Citation Record

Observation c6ff8555-3179-4b33-837b-7b521a4e9238 · outbound

This paper cites Resilient distributed vector consensus using centerpoint.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Resilient distributed vector consensus using centerpoint

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.356773Z

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Observation cfc28767-e6e6-47ed-a90e-54659f9b29d0 · outbound

This paper cites A little is enough: Circumventing defenses for distributed learnin g.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning A little is enough: Circumventing defenses for distributed learnin g

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.340996Z

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Observation 93244567-32b8-4f0c-8647-8a9c0bee824f · outbound

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

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Priva te empirical risk minimization: Eﬃcient algorithms and tight error bounds

Reference 3

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Observation 742b2c88-5020-4e59-8363-672f6c1f08af · outbound

This paper cites Bounds on the sample complexity for private learning and private data release.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Bounds on the sample complexity for private learning and private data release

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.307664Z

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Observation 78d9047a-3cc6-4b08-85c5-f9c2405e2cb8 · outbound

This paper cites Machine learning with adversaries: Byzantine tolerant gradient descent.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Machine learning with adversaries: Byzantine tolerant gradient descent

Reference 5

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Observation 93a07f54-ca3b-4aaa-ac62-8b2ba12b141b · outbound

This paper cites Optimization methods for large-scale machine learning.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Optimization methods for large-scale machine learning

Reference 6

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Observation 3b2cafe7-fe5d-4b08-9238-2c934aab87c1 · outbound

This paper cites An optimal randomized algorithm for maximum tukey depth.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning An optimal randomized algorithm for maximum tukey depth

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.258564Z

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Observation 6800431d-61dc-47de-8ba8-44ef2f5dd237 · outbound

This paper cites Distributed statistical machine learning in adversarial settings: Byz antine gradient descent.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Distributed statistical machine learning in adversarial settings: Byz antine gradient descent

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.243039Z

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Observation bc285af2-0282-43b7-a8c7-aadbfba49287 · outbound

This paper cites Privacy ampliﬁcati on by decentralization.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Privacy ampliﬁcati on by decentralization

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.227145Z

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Observation e3856e14-ed6c-40b6-819e-c8a48affe7ee · outbound

This paper cites Diﬀerentially private decentralized learning with random walks.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Diﬀerentially private decentralized learning with random walks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.211692Z

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Observation da0b0bab-4092-4a45-9e2d-ab6186892d92 · outbound

This paper cites Muﬄiato: Peer-to-peer privacy ampliﬁcation for decentralized optimization and averaging.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Muﬄiato: Peer-to-peer privacy ampliﬁcation for decentralized optimization and averaging

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.195731Z

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Observation 308bdad7-412f-4436-a01e-1339eab926a8 · outbound

This paper cites Hell y’s theorem and its relatives.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Hell y’s theorem and its relatives

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.179481Z

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Observation 54aa5da8-88d6-4e95-90a2-9810e0d61aaa · outbound

This paper cites Large scale distributed deep networks.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Large scale distributed deep networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.162759Z

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Observation b50d58d6-a6b0-49fe-87de-0c176bf36cca · outbound

This paper cites The algorithmic foundations of diﬀerential privacy.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning The algorithmic foundations of diﬀerential privacy

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.146588Z

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Observation e8073d6e-109f-4bc0-9f91-5aa23fe898c2 · outbound

This paper cites Bridge: Byzantine-resilient decentralized gradient descent.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Bridge: Byzantine-resilient decentralized gradient descent

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.130540Z

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Observation 9352230d-4d9c-43c4-8cd5-893e0d11ae49 · outbound

This paper cites Local model poisoning attacks to byzantine-robust federat ed learning.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Local model poisoning attacks to byzantine-robust federat ed learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.113812Z

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Observation 6074d299-3bf6-4938-8f95-2709d43df90a · outbound

This paper cites Byzantine- robust decentralized federated learning.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byzantine- robust decentralized federated learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.098360Z

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Observation 5789c9e5-ee74-4bf3-aabb-87445a64fbcf · outbound

This paper cites Model inversion attacks that exploit conﬁdence informatio n and basic countermeasures.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Model inversion attacks that exploit conﬁdence informatio n and basic countermeasures

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.083149Z

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Observation 530377a9-fd13-4797-bc16-7aba760e8e1f · outbound

This paper cites Privacy-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Privacy-Preserving Aggregation for Decentralized Learning with Byzantine-Robustness

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T19:51:57.151663Z

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Observation 98cb30f7-bfc4-4cf8-9912-f91ccee8f174 · outbound

This paper cites The hidde n vulnerability of distributed learning in byzantium.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning The hidde n vulnerability of distributed learning in byzantium

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.067205Z

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Observation afd5ce63-df85-4d4e-a048-2d20d7fb0863 · outbound

This paper cites Gradvit: Gradient inversion of vision transformers.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Gradvit: Gradient inversion of vision transformers

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.050821Z

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Observation c03d6168-e9c1-4306-83b3-4d5490052fe7 · outbound

This paper cites Byzantine-Robust Decentralized Learning via ClippedGossip.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byzantine-Robust Decentralized Learning via ClippedGossip

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T19:51:57.168929Z

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Observation 6e950416-faca-4719-8630-5780521fc902 · outbound

This paper cites What can we learn privately? SIAM Journal on Computing , 40(3):793–826, 2011.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning What can we learn privately? SIAM Journal on Computing , 40(3):793–826, 2011

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.032928Z

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Observation a4ed7df5-c987-405f-a6d4-4885aa217261 · outbound

This paper cites Revisiting gradient clipping: Stochastic bias and t ight convergence guarantees.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Revisiting gradient clipping: Stochastic bias and t ight convergence guarantees

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.017486Z

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Observation 68e1c3ab-7cf1-45af-8644-87d3e9fa6b79 · outbound

This paper cites A uniﬁed theory of decentralize d sgd with changing topology and local updates.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning A uniﬁed theory of decentralize d sgd with changing topology and local updates

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:58.002125Z

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Observation c8dc2363-398c-4722-8839-a10bb797b20d · outbound

This paper cites Resilient asymptotic consensus in robust networks.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Resilient asymptotic consensus in robust networks

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.986269Z

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Observation fab0351e-5743-4824-901f-e9f967deef30 · outbound

This paper cites Byzantine resilient distributed learning in multirobot systems.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byzantine resilient distributed learning in multirobot systems

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.970195Z

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Observation 5ddd4791-327b-40eb-a763-f1eac2875681 · outbound

This paper cites Can decentralized algorithms outperform centralized algorithms? a case study for decentralized par allel stochastic gradient descent.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Can decentralized algorithms outperform centralized algorithms? a case study for decentralized par allel stochastic gradient descent

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.953854Z

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Observation c501138b-160d-4166-967f-2c45f76435a6 · outbound

This paper cites Concentrated geo-privacy.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Concentrated geo-privacy

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.937290Z

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Observation 2fb834fc-64dd-48b3-bca5-d62ce4de76e8 · outbound

This paper cites Privacy- preserving decentralized federated learning over time-va rying communication graph.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Privacy- preserving decentralized federated learning over time-va rying communication graph

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.922223Z

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Observation 21e5e0fe-112a-4942-a2fe-52397a4cdce5 · outbound

This paper cites Multidimension al approximate agreement in byzantine asynchronous systems.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Multidimension al approximate agreement in byzantine asynchronous systems

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.907232Z

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Observation e1f1b29a-6414-4464-81ce-fd66786f7f02 · outbound

This paper cites R´ enyi diﬀerential privacy.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning R´ enyi diﬀerential privacy

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.891454Z

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Observation f9a2d164-8579-49ff-9b53-09dc6a65f56d · outbound

This paper cites Fault-tolerant rendezvous of multirobot systems.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Fault-tolerant rendezvous of multirobot systems

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.874552Z

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Observation 3311a323-647c-4298-8627-e6b73826076c · outbound

This paper cites On measures of entropy and information.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning On measures of entropy and information

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.859254Z

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Observation 6b911d88-e81c-4093-9355-9b7b3adf70cd · outbound

This paper cites A scala ble approach for privacy-preserving collaborative machine learning.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning A scala ble approach for privacy-preserving collaborative machine learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.842660Z

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Observation 44d0f507-e8b2-46ad-a75b-6ec88935f6b0 · outbound

This paper cites Training very deep networks.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Training very deep networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.827201Z

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Observation 0ef1200b-4f6d-4acc-a2e9-a08119b45f9a · outbound

This paper cites Decentralized federated averaging.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Decentralized federated averaging

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.811173Z

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Observation 2cc2009a-d398-4a29-b204-080f37777c6e · outbound

This paper cites Iterative byzantine vector consensus in incomplete graphs.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Iterative byzantine vector consensus in incomplete graphs

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.796109Z

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Observation 6ec4db86-3b34-4ea6-8a6d-ad85f67cbea6 · outbound

This paper cites A Resilient Convex Combination for consensus-based distributed algorithms.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning A Resilient Convex Combination for consensus-based distributed algorithms

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-15T19:51:57.468717Z

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Observation 14295073-ec68-4d8a-afb8-c808bbd80f69 · outbound

This paper cites Tailoring gradient methods for diﬀerentially private distributed optimizati on.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Tailoring gradient methods for diﬀerentially private distributed optimizati on

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.780560Z

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Observation 6b644ad8-d863-442f-b0cf-44948d9885e1 · outbound

This paper cites Byzantine- resilient decentralized stochastic optimization with rob ust aggregation rules.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byzantine- resilient decentralized stochastic optimization with rob ust aggregation rules

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.765352Z

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Observation 107c87f3-afa3-4892-ac43-8476ff866a1b · outbound

This paper cites Faba: an algorithm for fast aggregation against byzantine attacks in distributed neural networks.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Faba: an algorithm for fast aggregation against byzantine attacks in distributed neural networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.749986Z

Source-reported events for the cited work

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Observation ca904949-c828-413e-b835-c11b6bf8f144 · outbound

This paper cites A(DP) 2SGD: Asynchronous decentralized parallel stochastic gradient descent with diﬀerential privacy.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning A(DP) 2SGD: Asynchronous decentralized parallel stochastic gradient descent with diﬀerential privacy

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.735159Z

Source-reported events for the cited work

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Observation e89d1fc5-ec03-432b-a26c-de8c014f8aee · outbound

This paper cites Resilient multi-dimensional consensus in adversaria l environment.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Resilient multi-dimensional consensus in adversaria l environment

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.716252Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8075a8e3-7bbd-4ae6-b2f1-3890d2e74ae4 · outbound

This paper cites Byzantine-robust decentralized learning via remove-then-clip aggregation.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byzantine-robust decentralized learning via remove-then-clip aggregation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.700124Z

Source-reported events for the cited work

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Observation 2b13b457-8bbf-4711-811c-579cc583f61a · outbound

This paper cites Byrdie: Byzantine- resilient distributed coordinate descent for decentraliz ed learning.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byrdie: Byzantine- resilient distributed coordinate descent for decentraliz ed learning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.684069Z

Source-reported events for the cited work

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Observation 44883e39-f00b-42e9-8eb0-13a5258e9a2d · outbound

This paper cites On the tradeoﬀ between privacy preservation and byzantine-robustness in decentralized learning.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning On the tradeoﬀ between privacy preservation and byzantine-robustness in decentralized learning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.666204Z

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Observation 2e2882cd-e4ae-48f4-b0dc-f811834b2d73 · outbound

This paper cites Interior point algorithms: theory and analysis.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Interior point algorithms: theory and analysis

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.648486Z

Source-reported events for the cited work

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Observation 237b227d-d6f8-4e43-9a5d-a128e67c58c8 · outbound

This paper cites Byzantine-robust distributed learning: Toward s optimal statistical rates.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Byzantine-robust distributed learning: Toward s optimal statistical rates

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.631088Z

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Observation 17bafdfb-6296-4aba-8c17-1176860ed5b0 · outbound

This paper cites Subsampled r´ enyi diﬀerential privacy and analytical moments accountant.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Subsampled r´ enyi diﬀerential privacy and analytical moments accountant

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.612371Z

Source-reported events for the cited work

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Observation 9fce5f06-6d24-48f9-8098-1e57cbaf1aec · outbound

This paper cites Admm based privacy-preserving decentralized optimizatio n.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Admm based privacy-preserving decentralized optimizatio n

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.595182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6ffedcdb-a64b-4ffc-bcd7-bc8578035661 · outbound

This paper cites The secret revealer: Generative model-inversion attacks against deep neural networks.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning The secret revealer: Generative model-inversion attacks against deep neural networks

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.577696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9a2ba5da-c2ec-4b9e-b4e6-12faee81ae17 · outbound

This paper cites iDLG: Improved Deep Leakage from Gradients.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning iDLG: Improved Deep Leakage from Gradients

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T19:51:57.363769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a96716a-237d-4d50-8a77-9952f7bb5a09 · outbound

This paper cites Pvd-ﬂ: A privacy-preserving and veriﬁable decentralized federated learning framework.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Pvd-ﬂ: A privacy-preserving and veriﬁable decentralized federated learning framework

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.553941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation da2f047b-7bd6-4aa8-96c9-9bf768b71a90 · outbound

This paper cites Deep leakage from gradients.

ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Deep leakage from gradients

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T19:51:57.535309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers