Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T15:55:51.028880Z
Paper Citation Record · LEDGER
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis
As of 23 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2501.13648.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
18 of 18 outbound references displayed
- verified exact1
- verified fuzzy12
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b0adb9fc-4e51-4551-8d3e-8d66a7a79efb · outbound
This paper cites An Online-Learning Approach to Inverse Optimization.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis An Online-Learning Approach to Inverse Optimization
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:55:50.960830Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c91b36c-30a3-4739-a969-733b977739bb · outbound
This paper cites □ B Recovering the Same Bound as Bärmann et al.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis □ B Recovering the Same Bound as Bärmann et al
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.148607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9232ace4-6fdb-4b1b-bdef-f7fe39b80d94 · outbound
This paper cites Inverse problem theory: Methods for data fitting and model parameter estimation.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Inverse problem theory: Methods for data fitting and model parameter estimation
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.183230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cfaed048-6a51-431a-900f-ee162c90e1d6 · outbound
This paper cites an unresolved cited work.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T15:55:51.159605Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4515eda3-dec4-4ae7-8c2e-4d459fa0c56a · outbound
This paper cites We let /u1D6FD/u1D447 +1 = /u1D6FD/u1D447 , which does not affect the analysis (Orabona, 2023, Remark 7.3).
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis We let /u1D6FD/u1D447 +1 = /u1D6FD/u1D447 , which does not affect the analysis (Orabona, 2023, Remark 7.3)
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.137954Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3796b22e-f919-4137-8a0e-5394cad7be44 · outbound
This paper cites an unresolved cited work.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T15:55:51.125873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d27b5b2c-2db8-43f9-b286-b3acdb1230f0 · outbound
This paper cites Smart “predict, th en optimize.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Smart “predict, th en optimize
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.246182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d5490d9e-2d42-47ec-b61a-97deff37c007 · outbound
This paper cites Online learn ing from optimal actions.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Online learn ing from optimal actions
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.271153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation abe8df67-4e07-4e15-b1e5-9b1666e6231e · outbound
This paper cites Logarithmic re gret algorithms for online convex optimization.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Logarithmic re gret algorithms for online convex optimization
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.233908Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 86f50a7b-7608-4c07-b827-0f01ac73e2e0 · outbound
This paper cites Onlin e structured prediction with Fenchel–Young losses and improved surrogate regret for online multiclass classi fication with logistic loss.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Onlin e structured prediction with Fenchel–Young losses and improved surrogate regret for online multiclass classi fication with logistic loss
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.208441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5bebc78b-3317-4493-ab49-adf676d1f73f · outbound
This paper cites Learning with differentiable pertub ed optimizers.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Learning with differentiable pertub ed optimizers
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.283327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d9dd1c0f-979c-48d6-a5ca-dba06a21d26e · outbound
This paper cites Melding the d ata-decisions pipeline: Decision-focused learning for combinatorial optimization.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Melding the d ata-decisions pipeline: Decision-focused learning for combinatorial optimization
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.170508Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f4df7d44-3c82-4bc7-84a2-b9f28985f200 · outbound
This paper cites The theory of max-min, with applicat ions.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis The theory of max-min, with applicat ions
Reference 97
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.259023Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ace538cb-9446-43fa-b9e7-5a4a56490dc3 · outbound
This paper cites Online Convex Optimization Perspective for Learning from Dynamically Revealed Preferences.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Online Convex Optimization Perspective for Learning from Dynamically Revealed Preferences
Reference 134
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:55:50.973632Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4bec5637-d635-4b32-a974-c6ba67807e9f · outbound
This paper cites Asymptotically efficient a daptive allocation rules.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Asymptotically efficient a daptive allocation rules
Reference 139
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.221154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5845a4c6-e113-4851-af41-04a649012fc1 · outbound
This paper cites Learning line ar programs from optimal decisions.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Learning line ar programs from optimal decisions
Reference 202
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T15:55:51.195994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5ea76408-5f42-42ea-94b1-30ba80e1894f · outbound
This paper cites Online Learning: A Modern Introduction Using Convex Optimization.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Online Learning: A Modern Introduction Using Convex Optimization
Reference 235
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T15:55:50.993925Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23a76792-c9d3-4eb7-9b7e-5dcb98c5f7f4 · outbound
This paper cites Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound.
Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel$-$Young Loss Perspective and Gap-Dependent Regret Analysis Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound
Reference 247
- Resolution
- verified exact
- local_arxiv, observed 2026-08-10T15:55:51.069392Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
No inbound Pith citation observations are available.