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Paper Citation Record · LEDGER

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret

As of 23 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2505.08982.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.08982 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:56:07.732818Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T18:24:34.878784Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-09T06:30:40.703957Z

Reference resolution

52 of 52 outbound references displayed

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  • verified fuzzy39
  • unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d0086ed0-c8d8-408b-91b8-8370c68990ef · outbound

This paper cites an unresolved cited work.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 1

Resolution
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Observation ded36794-60f2-4525-b55c-80785efba380 · outbound

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Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 2

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Observation b3916ed7-a388-4635-b293-f70dc1d80c18 · outbound

This paper cites State estimation for robotics.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret State estimation for robotics

Reference 3

Resolution
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Observation 0119a8bc-1f11-4b8b-92d6-ef300b26b74b · outbound

This paper cites A linear dynamical syste m model for text.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret A linear dynamical syste m model for text

Reference 4

Resolution
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Observation 9d32456e-e0c8-4d8e-be4d-a545072008ed · outbound

This paper cites Long short-term memory Kalman filters: Recurrent neural estimat ors for pose regularization.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Long short-term memory Kalman filters: Recurrent neural estimat ors for pose regularization

Reference 5

Resolution
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Observation d930a6bc-11af-427c-bea3-60f181128f54 · outbound

This paper cites Kalman and extended Kalman filters : Concept, derivation and proper- ties.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Kalman and extended Kalman filters : Concept, derivation and proper- ties

Reference 6

Resolution
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Observation 425980b8-aa1a-45a7-b333-2bbc778eb854 · outbound

This paper cites Cubature Kalman filters.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Cubature Kalman filters

Reference 7

Resolution
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Observation a6db91d1-f927-48c3-ad60-bb7d19310601 · outbound

This paper cites System identification.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret System identification

Reference 8

Resolution
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Source-reported events for the cited work

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Observation 4f7a70bd-326c-47ad-884d-b582062e2763 · outbound

This paper cites Fundamentals of adaptive filtering.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Fundamentals of adaptive filtering

Reference 9

Resolution
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Source-reported events for the cited work

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Observation a1c75025-f9fb-4943-a4fa-65f242910bdd · outbound

This paper cites Learning line ar dynamical systems via spectral filtering.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Learning line ar dynamical systems via spectral filtering

Reference 10

Resolution
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Source-reported events for the cited work

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Observation 5a842c1c-1d60-44e0-aa52-0ca5b4b66ac9 · outbound

This paper cites No-regret prediction in marginally stable systems.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret No-regret prediction in marginally stable systems

Reference 11

Resolution
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Source-reported events for the cited work

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Observation 0e1b568b-3e38-41e5-9327-21f05c4d646c · outbound

This paper cites an unresolved cited work.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 12

Resolution
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Observation 27b65db7-ad81-4928-b99f-fcb4a3b5618c · outbound

This paper cites Finite sample a nalysis of stochastic system iden- tification.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Finite sample a nalysis of stochastic system iden- tification

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 438f2f1d-c954-4bcf-8fd1-fc22e1d706f6 · outbound

This paper cites Non-asymptotic identification of l inear dynamical systems using multiple trajectories.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Non-asymptotic identification of l inear dynamical systems using multiple trajectories

Reference 14

Resolution
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Observation 15fe31e0-cf24-4b7e-99b3-e1bbd32d5754 · outbound

This paper cites Improved rates for prediction and identific ation of partially observed linear dy- namical systems.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Improved rates for prediction and identific ation of partially observed linear dy- namical systems

Reference 15

Resolution
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Source-reported events for the cited work

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Observation 67cef0fb-ebb7-4320-9aa8-3eddabee466d · outbound

This paper cites Gradient d escent learns linear dynamical systems.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Gradient d escent learns linear dynamical systems

Reference 16

Resolution
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Source-reported events for the cited work

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Observation 225c6cd0-1049-4b4a-a4bc-215e021deefd · outbound

This paper cites Recursive identificati on and adaptive prediction in linear stochastic systems.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Recursive identificati on and adaptive prediction in linear stochastic systems

Reference 17

Resolution
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Source-reported events for the cited work

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Observation 5abcc8ee-d06b-4962-a6a3-545fc2a2e6f0 · outbound

This paper cites On line learning for time series prediction.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret On line learning for time series prediction

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ae90cabf-635e-40cb-9a1d-ecc01307ad2c · outbound

This paper cites On-line learning of linear dynamical systems: Exponential forgetting in Kalma n filters.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret On-line learning of linear dynamical systems: Exponential forgetting in Kalma n filters

Reference 19

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 48c5dfab-cac5-4af9-9d6d-6c255dd360b1 · outbound

This paper cites SLIP: Learning to predict in unknown dynamical systems with long-term memory.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret SLIP: Learning to predict in unknown dynamical systems with long-term memory

Reference 20

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 321da4d4-4092-4c05-ae72-2ae19b40dc53 · outbound

This paper cites Regret Analysis with Almost Sure Convergence for OBF-ARX Filter.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Regret Analysis with Almost Sure Convergence for OBF-ARX Filter

Reference 21

Resolution
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Observation 4f04a4c8-ba88-4936-b110-40ea6aeccfd6 · outbound

This paper cites Conc urrent learning adaptive control with directional forgetting.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Conc urrent learning adaptive control with directional forgetting

Reference 22

Resolution
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Source-reported events for the cited work

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Observation bb9f0e34-3803-474a-9cf5-e43cedd46961 · outbound

This paper cites Online convex programming and gener alized infinitesimal gradient ascent.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Online convex programming and gener alized infinitesimal gradient ascent

Reference 23

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 3e437726-88af-439e-aa63-3e30ef5359f2 · outbound

This paper cites Online Linear Regression in Dynamic Environments via Discounting.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Online Linear Regression in Dynamic Environments via Discounting

Reference 24

Resolution
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Source-reported events for the cited work

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Observation e023c711-edef-45bb-9c76-e02bf4e7cffa · outbound

This paper cites Exponential convergence of recursive least squares with ex ponential forgetting factor.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Exponential convergence of recursive least squares with ex ponential forgetting factor

Reference 25

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 45328d91-f05b-4a8c-a67e-9dee7892c15a · outbound

This paper cites On the influence of the forgetting factor of the RLS adaptive filter i n system identification.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret On the influence of the forgetting factor of the RLS adaptive filter i n system identification

Reference 26

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ac345af5-6448-4784-ba81-dc21938e029e · outbound

This paper cites Generalized forgetti ng recursive least squares: Stability and robustness guarantees.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Generalized forgetti ng recursive least squares: Stability and robustness guarantees

Reference 27

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2657e229-5dfb-415a-a0c4-725f45cdc7a8 · outbound

This paper cites Algebraic Riccati Equations.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Algebraic Riccati Equations

Reference 28

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 45bd3f2f-7976-4f29-bf70-daa5959ad010 · outbound

This paper cites Consistency and asymptotic normal- ity of some subspace algorithms for systems without observe d inputs.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Consistency and asymptotic normal- ity of some subspace algorithms for systems without observe d inputs

Reference 29

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6e7b7255-6ebf-4ae4-b6e1-011ab90eb0db · outbound

This paper cites Applied regression analysis.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Applied regression analysis

Reference 30

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c6291094-473a-4520-8d7c-b16510330357 · outbound

This paper cites Logistic regression: The importance of being improper.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Logistic regression: The importance of being improper

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 491b1f56-ecec-4322-9e3e-cb37c667862a · outbound

This paper cites Prediction, learning, and games.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Prediction, learning, and games

Reference 32

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:07.661355Z digest=sha256:dedc361fb40c1b058db3e80430551074d2ef8077cde580c69c5bd2a161e2cca0

Observation f0e7c3ae-ce0a-4b34-8e39-5cc086ee63bf · outbound

This paper cites A robust variable forgetting factor recursive least-squares algorithm for system identificati on.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret A robust variable forgetting factor recursive least-squares algorithm for system identificati on

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 6bb0bd51-db2a-448a-b7d5-57555026af55 · outbound

This paper cites Discounted a daptive online learning: Towards better regularization.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Discounted a daptive online learning: Towards better regularization

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.988406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.667815Z digest=sha256:8c75d3695e20cbc95f4c39ee2e5b9171a67af9b7280ce0f80641ffeb8d7f7a42

Observation b62f2d3e-cf87-4d24-a8db-7f32bc3d5e02 · outbound

This paper cites Predictive Linear Online Tracking for Unknown Targets.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Predictive Linear Online Tracking for Unknown Targets

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-15T21:56:07.768945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.670904Z digest=sha256:03cfe4a49a03f99c11369adee04071bdf86084ac57dbdd0250b2c10e5856e55e

Observation 1c06ea74-afae-4bd6-bc9e-b49ed2329746 · outbound

This paper cites Improved algorithms for linear stochastic bandits.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Improved algorithms for linear stochastic bandits

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.977967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.675609Z digest=sha256:6d9ba92fa97f26ad5caf5454ef16d282f461ca1180c849943eaf268a715c94b0

Observation 2eae233a-b1f3-423d-9e7d-6a6d09034278 · outbound

This paper cites Ridge regression: B iased estimation for nonorthogonal problems.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Ridge regression: B iased estimation for nonorthogonal problems

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.967536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.679011Z digest=sha256:aa67421029744fc39dac3488983c970f64ee9907254bfe1faa2b07f44bf4f658

Observation b42849a4-788b-41f5-a60f-8e388f010398 · outbound

This paper cites A bound on tail p robabilities for quadratic forms in independent random variables.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret A bound on tail p robabilities for quadratic forms in independent random variables

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.957508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.682062Z digest=sha256:74194fbb7640f0fadd98595709b418c010de6abe22a685a9a53bbde8328abf9b

Observation 993828c2-2e14-45cc-8c22-48055fd9bbfd · outbound

This paper cites High-dimensional probability: An introduction with appli cations in data science, volume 47.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret High-dimensional probability: An introduction with appli cations in data science, volume 47

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-15T21:56:07.685881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:07.685881Z digest=sha256:7a0be1a71a90fc7ba8325d254ff3410082a1a9a3541185f9949f9a0db993d0d0

Observation 0c5c9948-66de-4fac-a19d-5fd03f5b4a94 · outbound

This paper cites Cattivelli and Ali H.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Cattivelli and Ali H

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.940804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.688981Z digest=sha256:b12131ac33e1b8369d152bbf2de0884ab3e6c1523ba4f2b2e19571f93b5a0fcd

Observation ac840d8a-a7be-4c3d-84d3-bc6346d5357e · outbound

This paper cites Willems’ funda mental lemma for nonlinear systems with koopman linear embedding.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Willems’ funda mental lemma for nonlinear systems with koopman linear embedding

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.929930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.692107Z digest=sha256:04e0e39557141db64831e944140f174bf3f34bd757c3a32f17db3b4f8762e971

Observation 1160d16b-5ada-4bc0-a7f3-c170adbe78c4 · outbound

This paper cites Adaptive estimat ion of a quadratic functional by model selection.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Adaptive estimat ion of a quadratic functional by model selection

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.919702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.695832Z digest=sha256:6abb754c4800160df051dea284ef57a3e61b5ea45efa089b2c13ddeda7a1004e

Observation 1c2b5bf8-b582-4660-968c-c8cf8520e5ce · outbound

This paper cites Sayed, and Babak Hassibi.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Sayed, and Babak Hassibi

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.907712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.698940Z digest=sha256:b2f1ffa54af64e8364ce5593f0658bc7b8826edfe38288ba2f5599205d5e7cea

Observation ff1a991f-77bb-4f9d-b0ca-1dd72cc9e8cc · outbound

This paper cites Stochastic processes, estimation, and control.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Stochastic processes, estimation, and control

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.897048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.702336Z digest=sha256:4d4a087ce540a16bcdc086035c3437d593adcd025346d603cc5dee4863e58c49

Observation ea1100a3-c7e1-4351-ba05-7e1cd0fcfb15 · outbound

This paper cites The steady-state performance of the above recursion satisfie s the discrete-time algebraic Riccati equation P =APA T +Q −APC T( CPC T +R )−1 CPA T.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret The steady-state performance of the above recursion satisfie s the discrete-time algebraic Riccati equation P =APA T +Q −APC T( CPC T +R )−1 CPA T

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.885246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.706256Z digest=sha256:ed0ce31512e63f678bbf37c8d5fa4696eb1213323ed26995318910a9a72f7b53

Observation 5ef6a52f-6f33-4c89-aa4e-f5e7ec8f989f · outbound

This paper cites Denoteek =yk − ˆyk as the prediction error, also called innovation, at time step k.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Denoteek =yk − ˆyk as the prediction error, also called innovation, at time step k

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.873677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.710186Z digest=sha256:65af7d56ad7ee142b3a4376b1213a40f8138c15e5e58b16635160eda5cf81c4d

Observation 58bab826-0927-4c26-949f-f89bd7e15d4a · outbound

This paper cites an unresolved cited work.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:56:07.863359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.714162Z digest=sha256:7c60c7141bfd53372a074aa572bb73fe69b5059d6aa849d1b5555f2e0def97b3

Observation 30bec8aa-a323-47c3-a1b2-ac4be51d0f1e · outbound

This paper cites While for the term det ˜Z22 = det   ˜V2Tl−2 − p′−1∑ k=p DpZk,pZ T k,pDp  , conditioned on the event EPE and EZ, we have ‖ ‖ ‖ ( ΓZ k,p )−1/2 Zk,p ‖ ‖ ‖ 2 ≤ √ mp + √ 2 log 4k δ1.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret While for the term det ˜Z22 = det   ˜V2Tl−2 − p′−1∑ k=p DpZk,pZ T k,pDp  , conditioned on the event EPE and EZ, we have ‖ ‖ ‖ ( ΓZ k,p )−1/2 Zk,p ‖ ‖ ‖ 2 ≤ √ mp + √ 2 log 4k δ1

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.851683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.717780Z digest=sha256:3ec030095e78b32e011c5945658bd9248f3d4dcb01769113f03ed438744091e9

Observation 81d17f54-88a4-467b-8f46-d81c06d73366 · outbound

This paper cites an unresolved cited work.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:56:07.840513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.721267Z digest=sha256:4b968d613bf821abdaf5aaabfd8754566314a43ece4ce87d8c1c7e7abaf04b9e

Observation 955eec53-f2e0-4e03-bfdf-46fe468106dd · outbound

This paper cites an unresolved cited work.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:56:07.829228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.725376Z digest=sha256:e9ce1053c91964ac5f52e31a88ffec54484976506dd06cdf01869a938068286d

Observation 29df953d-9a9c-4bc1-beea-da66bc49cdec · outbound

This paper cites an unresolved cited work.

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:56:07.817701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.729205Z digest=sha256:50886765475007b49bae8594ab27f571ea5ac9352b4f1fee08411227c64f67fd

Observation d45c72a5-d4c0-4e91-9af5-99e51d5df953 · outbound

This paper cites Together with the cross-term bound, we have for probability at lea st 1 − ( 3 + 5π2 6 ) δ1, there is RN ≤ poly ( M,m,β, log 1 δ1 ,d, ‖a‖2 ) log3(N ).

Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret Together with the cross-term bound, we have for probability at lea st 1 − ( 3 + 5π2 6 ) δ1, there is RN ≤ poly ( M,m,β, log 1 δ1 ,d, ‖a‖2 ) log3(N )

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:07.805895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-15T21:56:07.732818Z digest=sha256:d05065082faace97b9c4f643e4cd8a490c10889d8a26f67bf978c332e415db42

Pith citing papers

Observation b90249b7-8524-476c-9759-082d8df77eba · inbound

Online Nonstochastic Prediction: Logarithmic Regret via Predictive Online Least Squares cites this paper.

Online Nonstochastic Prediction: Logarithmic Regret via Predictive Online Least Squares Model-free Online Learning for the Kalman Filter: Forgetting Factor and Logarithmic Regret

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-09T06:30:40.717024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T18:24:34.878784Z digest=sha256:575a6202855302fd976cc6a7190cb7e78b856aa68ccc60fe9c3db154fc3ba795