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Paper Citation Record · LEDGER

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization

As of 21 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 3 inbound Pith citation observations for arXiv:2506.22332.

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

pith.paper-citation-record.v1
2506.22332 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:17:59.046050Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T00:56:13.855741Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T09:21:25.556906Z

Reference resolution

59 of 59 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6283fa3c-9a11-4208-83a8-0c2b2c851546 · outbound

This paper cites Trust-Region Methods on Riemannian Mani- folds.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Trust-Region Methods on Riemannian Mani- folds

Reference 1

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation bade81b3-b407-49a9-92fd-ea85a07ce6e0 · outbound

This paper cites A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization

Reference 2

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 4c5f896e-ae9f-44c6-a4da-b02a56aa1362 · outbound

This paper cites A proximal trust-region method for nonsmooth opti- mization with inexact function and gradient evaluations.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A proximal trust-region method for nonsmooth opti- mization with inexact function and gradient evaluations

Reference 3

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Observation 76004b88-6d89-4f42-a63d-122c18b4d2d6 · outbound

This paper cites A Fast Iterative Shrinkage-Thresholding Algorithm for Lin- ear Inverse Problems.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A Fast Iterative Shrinkage-Thresholding Algorithm for Lin- ear Inverse Problems

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9701cfec-83a2-4acb-88ac-37c71483099e · outbound

This paper cites Global Optimality of Local Search for Low Rank Matrix Recovery.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Global Optimality of Local Search for Low Rank Matrix Recovery

Reference 5

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Source-reported events for the cited work

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Observation 315e5f9a-5564-4d5d-b289-57cad882a3b2 · outbound

This paper cites PANTR: A Proximal Algorithm With Trust- Region Updates for Nonconvex Constrained Optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization PANTR: A Proximal Algorithm With Trust- Region Updates for Nonconvex Constrained Optimization

Reference 6

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Observation d495826a-4244-49e7-97d0-ca181f0c353e · outbound

This paper cites Proximal alternating linearized minimization for nonconvex and nonsmooth problems.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Proximal alternating linearized minimization for nonconvex and nonsmooth problems

Reference 7

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 1d5a4bd8-d3fd-47bd-a3e8-8fa37bcc094c · outbound

This paper cites Bonnans and A.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Bonnans and A

Reference 8

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Source-reported events for the cited work

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Observation 20ce7c56-b1d8-4f99-89a3-77a36b1316c6 · outbound

This paper cites Gradient Descent Provably Escapes Saddle Points in the Training of Shallow ReLU Networks.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Gradient Descent Provably Escapes Saddle Points in the Training of Shallow ReLU Networks

Reference 9

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Observation bec9a706-51da-45c6-bace-8f6d4a25e6dd · outbound

This paper cites an unresolved cited work.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Unresolved cited work

Reference 10

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Observation de51bee6-cf7d-4218-8a9c-3a076432fc2b · outbound

This paper cites Orthogonal Invariance and Identi- fiability.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Orthogonal Invariance and Identi- fiability

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 93297b93-b003-4085-85dd-ee168d863560 · outbound

This paper cites Geometrical interpretation of the predictor- corrector type algorithms in structured optimization problems.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Geometrical interpretation of the predictor- corrector type algorithms in structured optimization problems

Reference 12

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 9c560bc6-3f33-46f0-af38-3aab8d532a15 · outbound

This paper cites Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization

Reference 13

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Observation 4085bef4-f1c7-4e54-a932-dcde226598fa · outbound

This paper cites Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions

Reference 14

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 96de577c-bcf4-43b9-b4c4-8663c3f09318 · outbound

This paper cites Proximal Gradient Algorithms Under Local Lipschitz Gradient Continuity.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Proximal Gradient Algorithms Under Local Lipschitz Gradient Continuity

Reference 15

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Observation 03fb758c-7b40-4ad5-a432-7e92316528c9 · outbound

This paper cites Optimality, identifiability, and sensitivity.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Optimality, identifiability, and sensitivity

Reference 16

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Observation ba9d932e-a2f1-4c3b-b45b-a1a356a9f1ea · outbound

This paper cites Nonmonotone curvilinear line search methods for unconstrained optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Nonmonotone curvilinear line search methods for unconstrained optimization

Reference 17

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Observation 06b81ff3-be3a-4b9b-802c-95be181de112 · outbound

This paper cites No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis

Reference 18

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Observation 1a4ae9ab-9c88-4ad8-88ef-fbf5ce82cc81 · outbound

This paper cites Matrix Completion has No Spurious Local Minimum.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Matrix Completion has No Spurious Local Minimum

Reference 19

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Observation e89aee8d-f2f2-4e8d-b50b-111fc4b7a1b3 · outbound

This paper cites Exploiting negative curva- ture directions in linesearch methods for unconstrained optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Exploiting negative curva- ture directions in linesearch methods for unconstrained optimization

Reference 20

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Observation f62ee447-72ed-4406-baa1-801d14054c99 · outbound

This paper cites Riemannian trust-region methods for strict saddle func- tions with complexity guarantees.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Riemannian trust-region methods for strict saddle func- tions with complexity guarantees

Reference 21

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Observation 27229d41-5df5-4df5-93f2-8e522ac5c3b2 · outbound

This paper cites an unresolved cited work.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Unresolved cited work

Reference 22

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Observation a1a13998-5491-4d1e-b045-024a57f35436 · outbound

This paper cites Smoothness of Subgradient Mappings and Its Applications in Parametric Optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Smoothness of Subgradient Mappings and Its Applications in Parametric Optimization

Reference 23

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Observation 2fb2c1aa-2349-47b5-9b4c-cea3ece749be · outbound

This paper cites Identifying Active Constraints via Partial Smoothness and Prox-Regularity.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Identifying Active Constraints via Partial Smoothness and Prox-Regularity

Reference 24

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Observation ae556829-5993-4140-bec0-14050b7babc3 · outbound

This paper cites Functions and Sets of Smooth Substructure: Relationships and Examples.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Functions and Sets of Smooth Substructure: Relationships and Examples

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6e463155-5223-42a7-9e6f-50b660a3252f · outbound

This paper cites Nonsmooth Optimization with Smooth Substructure.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Nonsmooth Optimization with Smooth Substructure

Reference 26

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 7ff10e3a-04a9-464d-80db-740d86ed9ee3 · outbound

This paper cites Generalized Power Method for Sparse Principal Component Analysis.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Generalized Power Method for Sparse Principal Component Analysis

Reference 27

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 22cda36b-5cf2-4fd2-acca-6a6542ff75f5 · outbound

This paper cites First- order methods almost always avoid strict saddle points.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization First- order methods almost always avoid strict saddle points

Reference 28

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Observation ada898cc-785a-4245-90e6-824c570a22f5 · outbound

This paper cites Active Sets, Nonsmoothness, and Sensitivity.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Active Sets, Nonsmoothness, and Sensitivity

Reference 29

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f8d0dc90-f232-4092-8334-e8d3ca6f5e28 · outbound

This paper cites Partial Smoothness, Tilt Stability, and Generalized Hes- sians.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Partial Smoothness, Tilt Stability, and Generalized Hes- sians

Reference 30

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 94e85e27-1af5-4bda-8d97-ee42a113eae3 · outbound

This paper cites Convergence Rates of First-Order Operator Splitting Methods.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Convergence Rates of First-Order Operator Splitting Methods

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6102db4b-2c99-47cb-b838-1a5370114489 · outbound

This paper cites An inexact regularized proximal Newton method for nonconvex and nonsmooth optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization An inexact regularized proximal Newton method for nonconvex and nonsmooth optimization

Reference 32

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 77051d75-9b6e-4de9-b0ee-702c778a7d94 · outbound

This paper cites An Envelope for Davis–Yin Splitting and Strict Saddle-Point Avoidance.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization An Envelope for Davis–Yin Splitting and Strict Saddle-Point Avoidance

Reference 33

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raw_fallback, observed 2026-08-06T22:18:03.622287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:56.979677Z digest=sha256:51d1f1821bb04129f15d9c10d388d0c9a19802e88ddd2256021ce318fd989bfc

Observation 82c9250a-f88b-41f9-85b8-691d0243d5e4 · outbound

This paper cites Curvilinear Stabilization Techniques for Trun- cated Newton Methods in Large Scale Unconstrained Optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Curvilinear Stabilization Techniques for Trun- cated Newton Methods in Large Scale Unconstrained Optimization

Reference 34

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source=pdf_text observed=2026-08-06T22:17:57.050788Z digest=sha256:1e6cafd80103690009c6df87a6eab37fd8dff677a2cefeb683fe1e2d14433275

Observation f8bab8b5-4930-4054-b902-9020b944501b · outbound

This paper cites A modification of Armijo’s step-size rule for negative curvature.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A modification of Armijo’s step-size rule for negative curvature

Reference 35

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source=pdf_text observed=2026-08-06T22:17:57.063544Z digest=sha256:84cedce580cbe54a5eb8d7f283cf4e9c9a164efafe8a743b6c83030c590f109f

Observation 9a3ca3fc-34f4-432d-9e6e-633e941b21e1 · outbound

This paper cites Primal-Dual Gradient Structured Functions: Second- Order Results; Links to Epi-Derivatives and Partly Smooth Functions.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Primal-Dual Gradient Structured Functions: Second- Order Results; Links to Epi-Derivatives and Partly Smooth Functions

Reference 36

Resolution
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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.182824Z digest=sha256:96764252829f018ed50f49e0041f6f2bdabf45a3d5105be26078e4309ef04f27

Observation 929b17db-cbf0-417f-8c30-863fba2f29df · outbound

This paper cites On the use of directions of negative curvature in a modified newton method.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization On the use of directions of negative curvature in a modified newton method

Reference 37

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source=pdf_text observed=2026-08-06T22:17:57.225111Z digest=sha256:97a9b4d04a15573292504fbb51e634c9b506893fbe4f44e7f77189ffd372f08f

Observation fa5d71fc-e861-4dc3-9388-d6f924f918a6 · outbound

This paper cites Nocedal and S.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Nocedal and S

Reference 38

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source=pdf_text observed=2026-08-06T22:17:57.302068Z digest=sha256:59ee5f4bc40298ba2e93f56cbb75ed1e45a4b0c5dd66e39bdfebfbc84428db39

Observation b7ab57c4-09c0-45aa-a42c-ea02e4982294 · outbound

This paper cites A trust region-type normal map-based semismooth New- ton method for nonsmooth nonconvex composite optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A trust region-type normal map-based semismooth New- ton method for nonsmooth nonconvex composite optimization

Reference 39

Resolution
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raw_fallback, observed 2026-08-06T22:18:02.707920Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.395123Z digest=sha256:9b612a070b8752705af421a778b5f2ce50445b5f234dfe49539c388cb92373bd

Observation f007c00d-1f2d-4917-84a6-c73f34298c71 · outbound

This paper cites Proximal Newton methods for convex composite op- timization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Proximal Newton methods for convex composite op- timization

Reference 40

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source=pdf_text observed=2026-08-06T22:17:57.416544Z digest=sha256:c1bae7481c177f0ab93f36611beba0066b8f72569bb2e92bab298a17bb497fb6

Observation f8b43161-3208-4c9c-9a27-310477fcf651 · outbound

This paper cites Generalized Hessian Properties of Regularized Nonsmooth Functions.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Generalized Hessian Properties of Regularized Nonsmooth Functions

Reference 41

Resolution
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raw_fallback, observed 2026-08-06T22:18:02.394577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.514997Z digest=sha256:ac0da1cbcd436fef48ad211108391dce98639b55731bd347df7d92bfc652f339

Observation c571b8eb-5dc0-4b83-b667-9fb30c40e86a · outbound

This paper cites Prox-regular functions in variational analysis.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Prox-regular functions in variational analysis

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:02.260972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.597813Z digest=sha256:28174a7cc6108ddec833e5c105b653ff9b41edd9424ed4b08430ac99a50acb58

Observation 6b172d2e-653b-4bbe-b90d-7e235ce1ffef · outbound

This paper cites First- and Second-Order Epi-Differentiability in Nonlinear Program- ming.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization First- and Second-Order Epi-Differentiability in Nonlinear Program- ming

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:02.063865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.684660Z digest=sha256:eddfc13e85945c67f651dc5822ffb3d097b27cb97cf0cc9e77c301de0773ea06

Observation 35b9ffa3-4d78-4430-b50e-d8a7a555e020 · outbound

This paper cites an unresolved cited work.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:18:01.895881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.793596Z digest=sha256:531577000f667840feac9ae7dfb936629f30b6ccb8885a48373299384fd6d7b3

Observation c435a1bf-15d6-4c21-85db-ae4e0fae5e51 · outbound

This paper cites On a Class of Nonsmooth Composite Functions.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization On a Class of Nonsmooth Composite Functions

Reference 45

Resolution
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raw_fallback, observed 2026-08-06T22:18:01.751702Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T22:17:57.831723Z digest=sha256:b097e01a89c65c1def00489833d12bc27edee900ccb5876b1ac36bca93c9e9ad

Observation cc9cc3b4-14aa-4bf2-9598-3d246c400547 · outbound

This paper cites A Family of Trust-Region-Based Algo- rithms for Unconstrained Minimization with Strong Global Convergence Properties.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A Family of Trust-Region-Based Algo- rithms for Unconstrained Minimization with Strong Global Convergence Properties

Reference 46

Resolution
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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:57.950349Z digest=sha256:81b6853a92ebe4f3d88c8f42a18134eea61ef5a767a2e6a0518a8a7f3f17d911

Observation b2e557c6-964d-4b43-8922-7e88a244904b · outbound

This paper cites Theoretical Insights Into the Opti- mization Landscape of Over-Parameterized Shallow Neural Networks.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Theoretical Insights Into the Opti- mization Landscape of Over-Parameterized Shallow Neural Networks

Reference 47

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.031156Z digest=sha256:017d121677e3fcf418a046d87581a9e41ad137d712931ed829a4d878ea49ab32

Observation 13910ac4-38bd-4e9d-a2ab-16fbb278614c · outbound

This paper cites The Conjugate Gradient Method and Trust Regions in Large Scale Op- timization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization The Conjugate Gradient Method and Trust Regions in Large Scale Op- timization

Reference 48

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.149904Z digest=sha256:7706c5db439a6806070226e5f2f3bd56cc8b40cae40b93ee524a05b0edc314fe

Observation 199bc42b-8a5b-46c2-ad4f-6972cac68f47 · outbound

This paper cites Forward–backward quasi-Newton methods for nonsmooth optimization problems.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Forward–backward quasi-Newton methods for nonsmooth optimization problems

Reference 49

Resolution
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source=pdf_text observed=2026-08-06T22:17:58.209364Z digest=sha256:7bad042f34816317e1142cda1d3575d1983e5a2ece1471b8e19a1bde3f656e9e

Observation 998b62ea-fa9a-4f41-a0c6-43e0a831d61c · outbound

This paper cites A simple and efficient algorithm for nonlinear model predictive control.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A simple and efficient algorithm for nonlinear model predictive control

Reference 50

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.353383Z digest=sha256:48bc88518b76493939fed0a77c769eaefc390fa7d32e3a63439b885e4875edb8

Observation 9f9d0143-fc1c-4869-925f-65e90739c8d1 · outbound

This paper cites A Geometric Analysis of Phase Retrieval.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A Geometric Analysis of Phase Retrieval

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:00.614258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.406047Z digest=sha256:4bfaba79f9234ecc9f26673d8f47bd94da843ee5950a43c1b0d2819bc98eea47

Observation 0de661c6-0579-48f0-8cd9-7551f59e1222 · outbound

This paper cites When Are Nonconvex Problems Not Scary?.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization When Are Nonconvex Problems Not Scary?

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T22:17:58.531907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:17:58.531907Z digest=sha256:35160187ea82ec2250a849570ac08ec852dcd3aea6920edff7467f3ef12eb138

Observation 2a45d166-6b33-4104-ae3b-83bf842fde31 · outbound

This paper cites On the Acceleration of Forward-Backward Splitting via an Inexact Newton Method.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization On the Acceleration of Forward-Backward Splitting via an Inexact Newton Method

Reference 53

Resolution
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raw_fallback, observed 2026-08-06T22:18:00.487807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.592207Z digest=sha256:0d5576b294b2a6504dd3357aa3f0126b29178e0ec5b8ab2a73c66c34b780881a

Observation 90591ff0-de9c-460e-b963-b1963a30569a · outbound

This paper cites A new envelope function for nonsmooth DC optimization.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization A new envelope function for nonsmooth DC optimization

Reference 54

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.721438Z digest=sha256:4e79b181177f64a978e9d6856d6d0fe1b5137cb50a0667ea6660ab9c23eedc02

Observation 9d050042-abda-43cb-b2be-ace4d1679b98 · outbound

This paper cites Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algo- rithms.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Forward-Backward Envelope for the Sum of Two Nonconvex Functions: Further Properties and Nonmonotone Linesearch Algo- rithms

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:00.175680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.792555Z digest=sha256:e2abb1638299f1be4eb45c1aaae8361381a0f4b49a6e313f19705c718d53fbf7

Observation 23bb0fc8-ee31-4b14-94a3-b87cfd4e2cdc · outbound

This paper cites Linear Regularizers Enforce the Strict Saddle Prop- erty.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Linear Regularizers Enforce the Strict Saddle Prop- erty

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:18:00.042860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.864099Z digest=sha256:5c3738760832c735389e3a6235c576cce476b250e2aa7a0cfb733e6d0ec30fc9

Observation 0e6e40e1-d6fe-4f31-b313-75a93b3fb841 · outbound

This paper cites Zhang, ed.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Zhang, ed

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:17:59.763990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.917536Z digest=sha256:f949a91a2d9f41ac171da138d725faa9710df52c4afd29c976bcd7161b397ec6

Observation 46815fb9-d5df-4be1-b4d9-a8d8feab55b6 · outbound

This paper cites Proximal gradient algorithm with trust region scheme on Riemannian manifold.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Proximal gradient algorithm with trust region scheme on Riemannian manifold

Reference 58

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raw_fallback, observed 2026-08-06T22:17:59.602631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:17:58.966620Z digest=sha256:647f26c28cfa987e1504e0d9d8e2d24f3352b7d6f1c50f0ec12c318a282993db

Observation 3b6b81d9-fead-4fb4-8433-a51b64403a78 · outbound

This paper cites Benign Nonconvex Landscapes in Optimal and Robust Control, Part II: Extended Convex Lifting.

Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization Benign Nonconvex Landscapes in Optimal and Robust Control, Part II: Extended Convex Lifting

Reference 59

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:17:59.046050Z digest=sha256:16c5059abaa4eba7e7321afb8080d3c3a629989b71f3f2a2d172fa24f0ff2345

Pith citing papers

Observation dd1670b6-e1a3-4d59-9c67-b7bc2f08bebb · inbound

PANOC-lite: A simpler and more efficient algorithm for composite minimization cites this paper.

PANOC-lite: A simpler and more efficient algorithm for composite minimization Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization

Reference 2

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arxiv_id, observed 2026-05-10T11:30:18.989208Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T11:26:20.231350Z digest=sha256:cb09f300598c602470cca3ea15a76db6e221f570be2843c02c5a51ce79232790

Observation 67b93aeb-cf1b-43e6-a74a-4403d15c45be · inbound

Quasar-Convex Optimization: Fundamental Properties and High-Order Proximal-Point Methods cites this paper.

Quasar-Convex Optimization: Fundamental Properties and High-Order Proximal-Point Methods Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization

Reference 2

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arxiv_id, observed 2026-05-12T09:21:25.558821Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T11:25:15.156063Z digest=sha256:2aaf5bfa73c01e880accd38223035c168f179a467962bc0ed25fcb33ddf441a9

Observation 4c4143a2-53e9-4e45-975d-a562fb7b7201 · inbound

Robust Learning Meets Quasar-Convex Optimization: Inexact High-Order Proximal-Point Methods cites this paper.

Robust Learning Meets Quasar-Convex Optimization: Inexact High-Order Proximal-Point Methods Second-order methods for provably escaping strict saddle points in composite nonconvex and nonsmooth optimization

Reference 32

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source=arxiv_source observed=2026-05-12T00:56:13.855741Z digest=sha256:592352a86e2b30bdc578906adc9bfac6756deae726d136d12d24c683aacc6ae0