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Paper Citation Record · LEDGER

Contextual Learning for Stochastic Optimization

As of 9 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2505.16829.

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

pith.paper-citation-record.v1
2505.16829 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:04:08.460029Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

  • verified exact2
  • verified fuzzy24
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ba893858-a2f1-4747-a77f-500942ab4e20 · outbound

This paper cites Taming the monster: A fast and simple algorithm for contextual bandits.

Contextual Learning for Stochastic Optimization Taming the monster: A fast and simple algorithm for contextual bandits

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.707621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.224888Z digest=sha256:13f805e68d1aa223eb8c2533e6bdfac3ca013dbecbb2cab984043ded4a0a77ac

Observation 71c1f5ea-7802-4d9b-98f9-d2b03e3f7fe4 · outbound

This paper cites Semi-bandit learning for monotone stochastic optimization.

Contextual Learning for Stochastic Optimization Semi-bandit learning for monotone stochastic optimization

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.653802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.306072Z digest=sha256:e8a70b67a157913824fac0a5638c60c726c3aa78d9007a7b02830f8119290250

Observation e2419198-beb3-4760-90cc-2e4e573743c1 · outbound

This paper cites Contextual pandora’s box.

Contextual Learning for Stochastic Optimization Contextual pandora’s box

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.584696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.390919Z digest=sha256:083bd827b6cc92c0ffabf98b4e6a1aebf40e695af558cdbcf48812cf51328591

Observation 24f0dcb3-0857-4003-baf1-8a7b0918e39d · outbound

This paper cites Multi-item mechanisms without item-independence: Learnability via robustness.

Contextual Learning for Stochastic Optimization Multi-item mechanisms without item-independence: Learnability via robustness

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.493232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.493541Z digest=sha256:d0534874faef59f770ffc2108239711bf01a50cfb95c6329284ff667617e8ba9

Observation 66541f08-2550-45a4-9ad0-3f7eb20c6607 · outbound

This paper cites Nonparametric pricing analytics with customer covariates.

Contextual Learning for Stochastic Optimization Nonparametric pricing analytics with customer covariates

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.416443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.580969Z digest=sha256:6661bbb89cde3c73c3fded4a486b567b09549db2fe7f76f754ace6e5287a44ff

Observation 604b8b84-ba73-4a04-808b-4ebd76d51a71 · outbound

This paper cites Contextual bandits with linear payoff functions.

Contextual Learning for Stochastic Optimization Contextual bandits with linear payoff functions

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.342906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.680263Z digest=sha256:a042bb6b8d99ac6310f77b9c1cbd2c72b140716516bdd032df438ca98994b2a1

Observation 7b0a4a27-619a-4d64-be38-83f1d7404f5d · outbound

This paper cites Cohen, Ilan Lobel, and Renato Paes Leme.

Contextual Learning for Stochastic Optimization Cohen, Ilan Lobel, and Renato Paes Leme

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.209175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.766503Z digest=sha256:7f95ad40024939de909efb80853c65240f2cb607662ff42460f35165e6cc80aa

Observation 17eb02f9-81a3-4ce5-8356-84275b67272d · outbound

This paper cites The sample complexity of revenue maximization.

Contextual Learning for Stochastic Optimization The sample complexity of revenue maximization

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:12.145841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.848385Z digest=sha256:a9cb58200e5a2469bf1f227a4ce88bd72aac621eb1a05de33575d0e06258f008

Observation bfccfe50-36f5-4462-a6b2-8b0680ea850c · outbound

This paper cites Prophet inequalities for independent and identically distributed random variables from an unknown distribution.

Contextual Learning for Stochastic Optimization Prophet inequalities for independent and identically distributed random variables from an unknown distribution

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.971477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.937983Z digest=sha256:3bf9492ec5c5eaa69718413e7187a0b63b91577fb4ea8855b35b6fbba01f1f53

Observation 64fc9806-31a8-4ce5-a061-5d996a1f37a5 · outbound

This paper cites The sample complexity of auctions with side information.

Contextual Learning for Stochastic Optimization The sample complexity of auctions with side information

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.818382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:06.990880Z digest=sha256:f3b5638f1a112e1739e0905ca96e0ba62b48e81a38d5d0f1546e01d350f7edc6

Observation 9fa99486-84ec-4408-a5d4-dc6c9e666b29 · outbound

This paper cites Efficient optimal leanring for contextual bandits.

Contextual Learning for Stochastic Optimization Efficient optimal leanring for contextual bandits

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.706089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.060155Z digest=sha256:eef87e92eb0cd2c0d7cdc61561f37fe59462968d67030efeedd5ca8177a0b735

Observation 8474fd59-2328-409e-8d4c-5390c1aa3b7d · outbound

This paper cites Posted pricing and prophet inequalities with inaccurate priors.

Contextual Learning for Stochastic Optimization Posted pricing and prophet inequalities with inaccurate priors

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.572431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.164398Z digest=sha256:9c6b702dd89aa39d3d84d66e691c06dc30444b9f9178e8aa55be18c093cb2a6b

Observation 69fe6b44-ca47-437d-ac6b-4f092eb7d2ec · outbound

This paper cites Practical contextual bandits with regression oracles.

Contextual Learning for Stochastic Optimization Practical contextual bandits with regression oracles

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.399287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.262706Z digest=sha256:dd3566df244d7955aa871632058a60931b3212a068c174e90fc32fe968b26c2a

Observation cf379dee-b170-463c-9614-64c1e8ea623a · outbound

This paper cites Bandit algorithms for prophet inequality and pandora's box.

Contextual Learning for Stochastic Optimization Bandit algorithms for prophet inequality and pandora's box

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.281715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.319928Z digest=sha256:4fbf847f198a1c8412b14e6dc0ece55210f32f0ebd2dbe63fb682728594faf13

Observation f8d2e820-fad7-4d0b-85d8-771c1be56d4b · outbound

This paper cites Online learning for min sum set cover and pandora’s box.

Contextual Learning for Stochastic Optimization Online learning for min sum set cover and pandora’s box

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.168464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.378413Z digest=sha256:821ecb726306c6ac08cbf6371240a4a19f8d62e8d74bc637bb64f457d24fc84e

Observation 319665ef-1851-47cd-958b-4ccb6118b0de · outbound

This paper cites On choosing and bounding probability metrics.

Contextual Learning for Stochastic Optimization On choosing and bounding probability metrics

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T15:04:07.438125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:04:07.438125Z digest=sha256:5614d733b5f9ea28c8e142116f02793e27ac65ff879778c98f2293c44c52da6d

Observation f63aabd0-1449-4f0b-9905-28c793af223a · outbound

This paper cites Generalizing complex hypotheses on product distributions: Auctions, prophet inequalities, and pandora’s problem.

Contextual Learning for Stochastic Optimization Generalizing complex hypotheses on product distributions: Auctions, prophet inequalities, and pandora’s problem

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:11.014023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.499022Z digest=sha256:be3b2a8f8fa603981177210465665c0ef120ce89a314ded5641cc155c52507eb

Observation 2bc15d16-af47-4c35-bbbb-fa5c35e4a0b1 · outbound

This paper cites Probability inequalities for sums of bounded random variables.

Contextual Learning for Stochastic Optimization Probability inequalities for sums of bounded random variables

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T15:04:07.599840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:04:07.599840Z digest=sha256:98e8d27fd97b39e536c030cc80d5ebc1c3da66a7d1c80dad788367a47afa21f5

Observation 117bf9fd-d77b-4f41-bc42-4bb527d169bc · outbound

This paper cites Dynamic pricing in high-dimensions.

Contextual Learning for Stochastic Optimization Dynamic pricing in high-dimensions

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:10.837060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.673515Z digest=sha256:a280d987714aa8e7d9c1981d0cb2c56ad0c27650a95f59a033ed347c42e9ae10

Observation 0a0be16e-240e-4a24-98e9-57052a3b918b · outbound

This paper cites Sample complexity of posted pricing for a single item.

Contextual Learning for Stochastic Optimization Sample complexity of posted pricing for a single item

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:10.759602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.752507Z digest=sha256:6b49107fab638c5127382ec0e41e44b0a58b67cdc30e3332f502357dfbabd328

Observation fa404ec8-d619-4a7b-8810-bab4b15d4fa4 · outbound

This paper cites The epoch-greedy algorithm for multi-armed bandits with side information.

Contextual Learning for Stochastic Optimization The epoch-greedy algorithm for multi-armed bandits with side information

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:10.618895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.846511Z digest=sha256:cca2c81597ba24018cb7c1c19f00c23a20362aa31cf14807b79630bafbf64d45

Observation 93b849b3-bf1b-44ae-9ad1-be32fadd313c · outbound

This paper cites Distribution-free contextual dynamic pricing.

Contextual Learning for Stochastic Optimization Distribution-free contextual dynamic pricing

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:10.327162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.921986Z digest=sha256:7fa77cbcf657139c976aadeb684bce765530cd9796be82862a7b1795f9b2d269

Observation 7e327a61-244f-4dfa-a6b3-0bb90f27c72b · outbound

This paper cites Ironing in the Dark.

Contextual Learning for Stochastic Optimization Ironing in the Dark

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:04:09.008170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:07.993104Z digest=sha256:eefc205f5434a9068ae4e93656d43fae035eb3ef576f0cf30f3336bdd8dfd47f

Observation 4521303f-b6db-4482-aebc-18b35cd93ca7 · outbound

This paper cites Learnability, stability and uniform convergence.

Contextual Learning for Stochastic Optimization Learnability, stability and uniform convergence

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:10.035376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:08.096549Z digest=sha256:17f6eb6ae6b883230bef79fa71caf651af3f81691b5908412792baf0a3eb13e3

Observation 32fdd793-ffee-45f7-ba4d-648d7379fa94 · outbound

This paper cites Bypassing the monster: A faster and simpler optimal algorithm for contextual bandits under realizability.

Contextual Learning for Stochastic Optimization Bypassing the monster: A faster and simpler optimal algorithm for contextual bandits under realizability

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T15:04:08.162193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:04:08.162193Z digest=sha256:179c9926d74f9ae65abf678acd0ee3669ff2c1cc827c288af31f8515c5c72e5d

Observation b09ef69b-bb59-48c1-afec-ab0a4b48cd47 · outbound

This paper cites Contextual bandits with packing and covering constraints: A modular lagrangian approach via regression.

Contextual Learning for Stochastic Optimization Contextual bandits with packing and covering constraints: A modular lagrangian approach via regression

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:09.781344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:08.235208Z digest=sha256:c9319deb4ef19fb1613f3c83c4a857853e4375dbcd40fffc1b09b1cb4ed3c589

Observation 8af057ab-f41c-41a6-8f90-8da824c29c4e · outbound

This paper cites Improved Algorithms for Contextual Dynamic Pricing.

Contextual Learning for Stochastic Optimization Improved Algorithms for Contextual Dynamic Pricing

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:04:08.756614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:08.331599Z digest=sha256:b9dc64dc9cbbd26c2b30ece797837b3a4507fe7424b018ebe0a5356f14406288

Observation ca0f23e9-5f65-4828-a957-d45b030f12bb · outbound

This paper cites The nature of statistical learning theory.

Contextual Learning for Stochastic Optimization The nature of statistical learning theory

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:09.527489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:08.403587Z digest=sha256:6f479dc05ef6c30b91a1e7e714858581aba2827286e04adab0935a7718d76f36

Observation 8668bfa3-5bbe-40d4-805f-605e7e78421c · outbound

This paper cites Weitzman.

Contextual Learning for Stochastic Optimization Weitzman

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T15:04:08.453247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:04:08.453247Z digest=sha256:378cb4ea66d563dd77c19cd55284aa11d04d7983069d7747b915ec3801d53d59

Observation a42e832f-fc90-405a-a34c-661d816b832d · outbound

This paper cites Towards agnostic feature-based dynamic pricing: Linear policies vs linear valuation with unknown noise.

Contextual Learning for Stochastic Optimization Towards agnostic feature-based dynamic pricing: Linear policies vs linear valuation with unknown noise

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:04:09.265381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-08-07T15:04:08.460029Z digest=sha256:bf8afaf2ef4b07a21fe607bf591a353882528ffe8e7c1c06cf5e4c8e67239c76

Pith citing papers

No inbound Pith citation observations are available.