Paper Citation Record · LEDGER

Stochastic AUC Maximization with Deep Neural Networks

As of 15 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 1 inbound Pith citation observation for arXiv:1908.10831.

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

pith.paper-citation-record.v1
1908.10831 v5

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:41:34.848326Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:38:21.793863Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T05:38:21.907456Z

Reference resolution

54 of 54 outbound references displayed

verified exact2
verified fuzzy23
unresolved28
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 50857d24-7b26-4430-86da-0776e6d82c4a · outbound

This paper cites A Convergence Theory for Deep Learning via Over-Parameterization.

Stochastic AUC Maximization with Deep Neural Networks A Convergence Theory for Deep Learning via Over-Parameterization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.627188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10edc41d-aa1d-4017-bdf9-f6527228fc45 · outbound

This paper cites A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks.

Stochastic AUC Maximization with Deep Neural Networks A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.632775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 330131e8-4198-4896-ae70-be3e3cc850ca · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Stochastic AUC Maximization with Deep Neural Networks Neural Machine Translation by Jointly Learning to Align and Translate

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.638332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7703291-0ff7-4312-8418-9732d0ba57ec · outbound

This paper cites Stability and Generalization of Learning Algorithms that Converge to Global Optima.

Stochastic AUC Maximization with Deep Neural Networks Stability and Generalization of Learning Algorithms that Converge to Global Optima

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:41:35.228489Z

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 0d4d65b9-7c50-4784-9e70-5cc71776280b · outbound

This paper cites Universal stagewise learning for non-convex problems with convergence on averaged solutions.

Stochastic AUC Maximization with Deep Neural Networks Universal stagewise learning for non-convex problems with convergence on averaged solutions

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.628708Z

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 b15282fc-bbf3-4d53-9f8f-a1b3ed4204fd · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Stochastic AUC Maximization with Deep Neural Networks BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.652638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef0e4598-fc11-428f-8e18-5b248ac8905a · outbound

This paper cites Gradient Descent Finds Global Minima of Deep Neural Networks.

Stochastic AUC Maximization with Deep Neural Networks Gradient Descent Finds Global Minima of Deep Neural Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.657220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e945dcf6-3ea2-4384-93c0-10b3fd9334e3 · outbound

This paper cites Gradient Descent Provably Optimizes Over-parameterized Neural Networks.

Stochastic AUC Maximization with Deep Neural Networks Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.661193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f787a4c-7fef-49e4-aa60-644ba232a0cc · outbound

This paper cites Adaptive subgradient methods for online learning and stochastic optimization.

Stochastic AUC Maximization with Deep Neural Networks Adaptive subgradient methods for online learning and stochastic optimization

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.664915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01dd087c-13e7-468c-9485-b0aad00aa297 · outbound

This paper cites Composite objective mirror descent.

Stochastic AUC Maximization with Deep Neural Networks Composite objective mirror descent

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.607388Z

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 78d00cd5-c19e-4133-b0b8-83e3490c5fa6 · outbound

This paper cites The foundations of cost-sensitive learning.

Stochastic AUC Maximization with Deep Neural Networks The foundations of cost-sensitive learning

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.595129Z

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 23897d99-5920-4f3b-9332-9b9852272866 · outbound

This paper cites One-pass auc optimization.

Stochastic AUC Maximization with Deep Neural Networks One-pass auc optimization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.584495Z

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 83331f5b-03fd-455b-aa6d-66138a73cfa8 · outbound

This paper cites Generating Sequences With Recurrent Neural Networks.

Stochastic AUC Maximization with Deep Neural Networks Generating Sequences With Recurrent Neural Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.680037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e145f71b-eb4e-4592-b225-f6aa15d18b19 · outbound

This paper cites A simple generalisation of the area under the roc curve for multiple class classification problems.

Stochastic AUC Maximization with Deep Neural Networks A simple generalisation of the area under the roc curve for multiple class classification problems

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.573153Z

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 a6e849fa-ec85-40f3-a111-e8c9cb1d3efd · outbound

This paper cites The meaning and use of the area under a receiver operating characteristic (roc) curve.

Stochastic AUC Maximization with Deep Neural Networks The meaning and use of the area under a receiver operating characteristic (roc) curve

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.559947Z

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 f0304677-fe6c-4e82-912d-7b0f06491e87 · outbound

This paper cites A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

Stochastic AUC Maximization with Deep Neural Networks A method of comparing the areas under receiver operating characteristic curves derived from the same cases

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.546915Z

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 3dbd4523-9b1e-43f6-8ff9-664465b498f1 · outbound

This paper cites Identity Matters in Deep Learning.

Stochastic AUC Maximization with Deep Neural Networks Identity Matters in Deep Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.697486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 813c97ca-2ef5-45d1-8d4a-25dacbc945da · outbound

This paper cites Deep residual learning for image recognition.

Stochastic AUC Maximization with Deep Neural Networks Deep residual learning for image recognition

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.701594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48adb466-0b79-4bb2-a20a-fcf9a573efe7 · outbound

This paper cites Deep neural networks for acoustic modeling in speech recognition.

Stochastic AUC Maximization with Deep Neural Networks Deep neural networks for acoustic modeling in speech recognition

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.705854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4e21477-1f14-4947-a95c-d1976b49943d · outbound

This paper cites What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?.

Stochastic AUC Maximization with Deep Neural Networks What is Local Optimality in Nonconvex-Nonconcave Minimax Optimization?

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.709578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9343a66b-bfa4-40e7-b289-f93855e378e1 · outbound

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

Stochastic AUC Maximization with Deep Neural Networks Linear convergence of gradient and proximal-gradient methods under the polyak- ojasiewicz condition

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.714315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 371264b0-cc00-472d-91a1-31b597c119c4 · outbound

This paper cites An Alternative View: When Does SGD Escape Local Minima?.

Stochastic AUC Maximization with Deep Neural Networks An Alternative View: When Does SGD Escape Local Minima?

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.718224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ee471dc-4822-4694-919a-faa1c0df68e7 · outbound

This paper cites Imagenet classification with deep convolutional neural networks.

Stochastic AUC Maximization with Deep Neural Networks Imagenet classification with deep convolutional neural networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.512314Z

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 c8a3f5c0-3137-4d4e-b0e8-1b43d3494ed1 · outbound

This paper cites Non-convex finite-sum optimization via scsg methods.

Stochastic AUC Maximization with Deep Neural Networks Non-convex finite-sum optimization via scsg methods

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.501054Z

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 e84b39d8-865b-49a6-8488-8ffc319a5cba · outbound

This paper cites Learning overparameterized neural networks via stochastic gradient descent on structured data.

Stochastic AUC Maximization with Deep Neural Networks Learning overparameterized neural networks via stochastic gradient descent on structured data

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.489499Z

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 636a9a10-62ec-4086-b266-1c32f77fe1b7 · outbound

This paper cites Convergence analysis of two-layer neural networks with relu activation.

Stochastic AUC Maximization with Deep Neural Networks Convergence analysis of two-layer neural networks with relu activation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.476837Z

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 6711c80e-0176-4a41-82f4-dbaac111c419 · outbound

This paper cites A simple proximal stochastic gradient method for nonsmooth nonconvex optimization.

Stochastic AUC Maximization with Deep Neural Networks A simple proximal stochastic gradient method for nonsmooth nonconvex optimization

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.465431Z

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 f42fe7e5-5445-4b62-9576-4c6805fa5566 · outbound

This paper cites First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems.

Stochastic AUC Maximization with Deep Neural Networks First-order Convergence Theory for Weakly-Convex-Weakly-Concave Min-max Problems

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.742183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c1ade9b-5161-4b01-bbbb-bfb81ae526b7 · outbound

This paper cites Fast stochastic auc maximization with o (1/n)-convergence rate.

Stochastic AUC Maximization with Deep Neural Networks Fast stochastic auc maximization with o (1/n)-convergence rate

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.453674Z

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 c8be1fbb-1c74-493c-98a8-051b0f20386e · outbound

This paper cites Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications.

Stochastic AUC Maximization with Deep Neural Networks Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-14T10:41:35.122474Z

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 df21cc64-d9f0-48e8-9269-c9eacb095d20 · outbound

This paper cites Acoustic modeling using deep belief networks.

Stochastic AUC Maximization with Deep Neural Networks Acoustic modeling using deep belief networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.441387Z

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 37e38b5c-9b91-4b6b-b634-1da4d972733c · outbound

This paper cites Stochastic proximal algorithms for auc maximization.

Stochastic AUC Maximization with Deep Neural Networks Stochastic proximal algorithms for auc maximization

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.429524Z

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 92f9e986-4d8c-49c7-aec1-4d672567d30e · outbound

This paper cites Robust stochastic approximation approach to stochastic programming.

Stochastic AUC Maximization with Deep Neural Networks Robust stochastic approximation approach to stochastic programming

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.761445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af410f7f-a3bc-41be-af4c-342f75ef9c25 · outbound

This paper cites Introductory lectures on convex optimization: A basic course, volume 87.

Stochastic AUC Maximization with Deep Neural Networks Introductory lectures on convex optimization: A basic course, volume 87

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.765265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45d40c13-af2c-448e-99db-c15f82ab4383 · outbound

This paper cites Stochastic Recursive Gradient Algorithm for Nonconvex Optimization.

Stochastic AUC Maximization with Deep Neural Networks Stochastic Recursive Gradient Algorithm for Nonconvex Optimization

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.769327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da331526-1a69-4ddb-abb2-2fedc82a8ed4 · outbound

This paper cites Gradient methods for minimizing functionals.

Stochastic AUC Maximization with Deep Neural Networks Gradient methods for minimizing functionals

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.401985Z

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 7a8f2219-79ec-4ae4-aa29-a825a400b4b0 · outbound

This paper cites Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning.

Stochastic AUC Maximization with Deep Neural Networks Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.777456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ce85653-22a3-4f27-b4d6-468689001f76 · outbound

This paper cites Stochastic variance reduction for nonconvex optimization.

Stochastic AUC Maximization with Deep Neural Networks Stochastic variance reduction for nonconvex optimization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.389758Z

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 f47ae651-b6d9-4f56-bada-89bdeb1802c1 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

Stochastic AUC Maximization with Deep Neural Networks Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.375979Z

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 46eb98ec-99d6-470a-8c5c-115b22757251 · outbound

This paper cites Monotone operators and the proximal point algorithm.

Stochastic AUC Maximization with Deep Neural Networks Monotone operators and the proximal point algorithm

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.360813Z

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 c9fec064-8024-4d09-baf8-43f512314f9a · outbound

This paper cites Solving Non-Convex Non-Concave Min-Max Games Under Polyak-{\L}ojasiewicz Condition.

Stochastic AUC Maximization with Deep Neural Networks Solving Non-Convex Non-Concave Min-Max Games Under Polyak-{\L}ojasiewicz Condition

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.793076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b93fa3ed-8362-4356-9560-9d80042840fc · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Stochastic AUC Maximization with Deep Neural Networks Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.797210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 597bb0a1-b4da-47df-a96f-7568583ebf05 · outbound

This paper cites Sequence to sequence learning with neural networks.

Stochastic AUC Maximization with Deep Neural Networks Sequence to sequence learning with neural networks

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.348385Z

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 e3dfdfc1-5f79-41d9-bcde-55de5bdff928 · outbound

This paper cites SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms.

Stochastic AUC Maximization with Deep Neural Networks SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.805848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53f37d68-1b6d-4307-a7c2-4ba6072083e5 · outbound

This paper cites Stochastic online auc maximization.

Stochastic AUC Maximization with Deep Neural Networks Stochastic online auc maximization

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.334470Z

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 d8687003-4a0e-4f95-a393-3fc9e6fd778a · outbound

This paper cites Online auc maximization.

Stochastic AUC Maximization with Deep Neural Networks Online auc maximization

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.318341Z

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 71fa6473-5068-44ad-ba3b-254e9a91f30b · outbound

This paper cites Stochastic nested variance reduced gradient descent for nonconvex optimization.

Stochastic AUC Maximization with Deep Neural Networks Stochastic nested variance reduced gradient descent for nonconvex optimization

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T10:41:35.303660Z

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 598cf54c-9e46-4430-98ab-611d38964c93 · outbound

This paper cites Characterization of Gradient Dominance and Regularity Conditions for Neural Networks.

Stochastic AUC Maximization with Deep Neural Networks Characterization of Gradient Dominance and Regularity Conditions for Neural Networks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.821062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85d72c24-c6dd-46a7-bc8b-c09c9bb2bc52 · outbound

This paper cites An Improved Analysis of Training Over-parameterized Deep Neural Networks.

Stochastic AUC Maximization with Deep Neural Networks An Improved Analysis of Training Over-parameterized Deep Neural Networks

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.825116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0eeea83-45dc-4a6f-948d-46a4be3a185f · outbound

This paper cites Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks.

Stochastic AUC Maximization with Deep Neural Networks Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.829076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9103c397-b9cf-4fba-90ec-5dcfa5cde6b9 · outbound

This paper cites write newline.

Stochastic AUC Maximization with Deep Neural Networks write newline

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.833067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ccb6a35-fcbd-409c-be27-5ed226185cab · outbound

This paper cites @esa (Ref.

Stochastic AUC Maximization with Deep Neural Networks @esa (Ref

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.838573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4bc5a95-2009-434d-b3e8-8d3f83af2d96 · outbound

This paper cites an unresolved cited work.

Stochastic AUC Maximization with Deep Neural Networks Unresolved cited work

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-14T10:41:34.843885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e962bfa-7284-4710-a63e-ce504e46afa8 · outbound

This paper cites 1h A XHT J e ,..b ] K Lxb-.

Stochastic AUC Maximization with Deep Neural Networks 1h A XHT J e ,..b ] K Lxb-

Reference 54

Resolution: malformed identifier; raw_fallback, observed 2026-08-14T10:41:35.014329Z

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.

Pith citing papers

Observation 9ebce470-4ddd-437e-bf81-1325dedb47a3 · inbound

Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning cites this paper.

Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning Stochastic AUC Maximization with Deep Neural Networks

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:38:21.913880Z

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.