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Stability of first-order methods in tame optimization

As of 13 August 2026, this Paper Citation Record lists 100 of 127 outbound references and 0 inbound Pith citation observations for arXiv:2412.00640.

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pith.paper-citation-record.v1
2412.00640 v1

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measured 100 of 127 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

100 of 127 outbound references displayed

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Outbound references

Observation 19036b5b-88f1-437f-b84f-444520c83231 · outbound

This paper cites Deep residual learning for image recognition,.

Stability of first-order methods in tame optimization Deep residual learning for image recognition,

Reference 1

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Stability of first-order methods in tame optimization An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 2

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Observation 4e1744ad-40cc-4c72-b7a2-027899f04278 · outbound

This paper cites Attention is all you need,.

Stability of first-order methods in tame optimization Attention is all you need,

Reference 3

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

Stability of first-order methods in tame optimization BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 4

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Observation c52ee23f-1e4b-4c71-9d8e-3bae752951b6 · outbound

This paper cites Language models are few-shot learners,.

Stability of first-order methods in tame optimization Language models are few-shot learners,

Reference 5

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Observation 9ee684cf-b140-48f4-8e29-1ec0b6e7b883 · outbound

This paper cites High-resolution image synthesis with latent diffusion models,.

Stability of first-order methods in tame optimization High-resolution image synthesis with latent diffusion models,

Reference 6

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Stability of first-order methods in tame optimization A stochastic approximation method,

Reference 7

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Observation 3a5bd3a2-781e-403c-881d-a381c593348c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Stability of first-order methods in tame optimization Adam: A Method for Stochastic Optimization

Reference 8

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Observation c7a540bb-bf7b-435a-b265-b2d8bc99425c · outbound

This paper cites An overview of gradient descent optimization algorithms.

Stability of first-order methods in tame optimization An overview of gradient descent optimization algorithms

Reference 9

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Observation 11fed02a-cc62-40c9-a390-d56d7425ea04 · outbound

This paper cites Large scale distributed deep networks,.

Stability of first-order methods in tame optimization Large scale distributed deep networks,

Reference 10

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Observation 135f1662-ed9d-420d-aab6-17725ec68544 · outbound

This paper cites Problème général de la stabilité du mouvement,.

Stability of first-order methods in tame optimization Problème général de la stabilité du mouvement,

Reference 11

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Observation 6f377155-eb90-433c-82b0-fff0de3ea398 · outbound

This paper cites Sastry, Nonlinear systems: analysis, stability, and control.

Stability of first-order methods in tame optimization Sastry, Nonlinear systems: analysis, stability, and control

Reference 12

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Observation 88b54bc1-066c-4595-8178-5f6e730c50ff · outbound

This paper cites van den Dries, Tame topology and o-minimal structures.

Stability of first-order methods in tame optimization van den Dries, Tame topology and o-minimal structures

Reference 13

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Observation 59f497b6-a15c-4cb6-97c6-cab0ee5fe558 · outbound

This paper cites An invitation to tame optimization,.

Stability of first-order methods in tame optimization An invitation to tame optimization,

Reference 14

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This paper cites Subdifferentiability of real functions,.

Stability of first-order methods in tame optimization Subdifferentiability of real functions,

Reference 15

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Observation 7d7c9330-3a56-4a34-94b0-080d9194e737 · outbound

This paper cites Friedman, T.

Stability of first-order methods in tame optimization Friedman, T

Reference 16

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Stability of first-order methods in tame optimization Generalized gradients and applications,

Reference 17

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Stability of first-order methods in tame optimization Unresolved cited work

Reference 18

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Stability of first-order methods in tame optimization Aubin and A

Reference 19

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Stability of first-order methods in tame optimization Unresolved cited work

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Observation 9c5d8914-aacf-4af3-87b9-e424448ea161 · outbound

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Stability of first-order methods in tame optimization Remarks on Tarski’s problem concerning ( R,+,∗, exp),

Reference 21

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Stability of first-order methods in tame optimization Definable sets in ordered structures. i,

Reference 22

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Stability of first-order methods in tame optimization Bochnak, M

Reference 23

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Stability of first-order methods in tame optimization Geometric categories and o-minimal structures,

Reference 24

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Stability of first-order methods in tame optimization Division d’une distribution par une fonction analytique de variables réelles,

Reference 25

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Observation 1055d010-da91-42ff-8f9d-d9abec382680 · outbound

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Stability of first-order methods in tame optimization Sur le problème de la division,

Reference 26

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Stability of first-order methods in tame optimization On the division of distributions by polynomials,

Reference 27

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Stability of first-order methods in tame optimization On gradients of functions definable in o-minimal structures,

Reference 28

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Observation 0e8d202e-fdd8-46d6-a33f-7a68c6bd621c · outbound

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Stability of first-order methods in tame optimization Clarke subgradients of stratifiable func- tions,

Reference 29

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Stability of first-order methods in tame optimization Proximal alternating minimization and projection methods for nonconvex problems: An approach based on the Kurdyka- Łojasiewicz inequality,

Reference 30

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Stability of first-order methods in tame optimization Global convergence of the gradient method for functions definable in o-minimal structures,

Reference 31

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Stability of first-order methods in tame optimization Curves of descent,

Reference 32

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Stability of first-order methods in tame optimization Stochastic subgradient method converges on tame functions,

Reference 33

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Stability of first-order methods in tame optimization Optimization methods for large-scale machine learning,

Reference 34

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Stability of first-order methods in tame optimization Nonconvex Robust Low-Rank Matrix Recov- ery,

Reference 35

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Stability of first-order methods in tame optimization Global convergence of sub-gradient method for robust matrix re- covery: Small initialization, noisy measurements, and over-parameterization,

Reference 36

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Stability of first-order methods in tame optimization Accelerating SGD for Highly Ill-Conditioned Huge-Scale Online Matrix Completion,

Reference 37

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Stability of first-order methods in tame optimization Deep learning,

Reference 38

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Stability of first-order methods in tame optimization Sur l’Equation à l’Aide de Laquelle on Détermine les Inégalités Sécu- laires,

Reference 39

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Observation b5a55893-8d6b-48c9-98d3-1290ff43e7ed · outbound

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Stability of first-order methods in tame optimization Continuous time analysis of momentum methods,

Reference 40

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Observation fefa8cc5-9c9b-422e-8c57-50ed28b0721f · outbound

This paper cites Some methods of speeding up the convergence of iteration methods,.

Stability of first-order methods in tame optimization Some methods of speeding up the convergence of iteration methods,

Reference 41

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source=pdf_text observed=2026-08-12T05:16:51.371779Z digest=sha256:bb2b041a33a0e08bf456dae45088be882b16686551ddb877161cfcc6bbd96471

Observation 05fe9f29-8e1b-47d9-bb09-9b0a3189dd0f · outbound

This paper cites Nesterov, Lectures on Convex Optimization.

Stability of first-order methods in tame optimization Nesterov, Lectures on Convex Optimization

Reference 42

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source=pdf_text observed=2026-08-12T05:16:51.375887Z digest=sha256:fe261095bce73c271e9830f310062a125d8186c5674e166c85919962ef712c15

Observation 46c16fe8-8847-4399-8824-07bc42e09435 · outbound

This paper cites Shor, “Application of the gradient method for the solution of network transportation problems.

Stability of first-order methods in tame optimization Shor, “Application of the gradient method for the solution of network transportation problems

Reference 43

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source=pdf_text observed=2026-08-12T05:16:51.380428Z digest=sha256:40a8c588226ed35e4e8d03fc46eb588155f2ca3a9e5f5152cd828597007125b0

Observation 6e97949e-7543-4ac0-9366-956e877e680f · outbound

This paper cites On the structure of algorithms for numerical solution of problems of optimal planning and design,.

Stability of first-order methods in tame optimization On the structure of algorithms for numerical solution of problems of optimal planning and design,

Reference 44

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source=pdf_text observed=2026-08-12T05:16:51.385183Z digest=sha256:f27087b085660bbbbae4d97dcbd2f6f398b7f2d72ec694a9fb2f6d27385bdb32

Observation 7b4c0c11-94c1-4ecc-81ce-a063a51747ef · outbound

This paper cites Bertsekas, Convex optimization algorithms.

Stability of first-order methods in tame optimization Bertsekas, Convex optimization algorithms

Reference 45

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source=pdf_text observed=2026-08-12T05:16:51.388986Z digest=sha256:b3dfc00468ed77def07263ec94c50e2e1a3db23eb68fde8610c5eb771740a3ba

Observation 5b2e4baf-8c10-4f37-8bc6-94a6f8dcf9be · outbound

This paper cites A method for solving the convex programming problem with convergence rate𝑂(1/𝑘2),.

Stability of first-order methods in tame optimization A method for solving the convex programming problem with convergence rate𝑂(1/𝑘2),

Reference 46

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source=pdf_text observed=2026-08-12T05:16:51.392841Z digest=sha256:5aa8981182a1d64c69d24bff21849425bed17c53704907411e5c2828a0f8163b

Observation 2dcba610-29f9-470f-8b44-eed03b43b32a · outbound

This paper cites Heavy-ball method in nonconvex optimization problems,.

Stability of first-order methods in tame optimization Heavy-ball method in nonconvex optimization problems,

Reference 47

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.396773Z digest=sha256:b242b137f19c71b6cb753edcff876ef5c1b52ec6ece2fa248850c60dbab8a337

Observation 6ffc5ce9-5187-4ede-8c6a-c021182acdd5 · outbound

This paper cites iPiano: Inertial proximal algorithm for nonconvex optimization,.

Stability of first-order methods in tame optimization iPiano: Inertial proximal algorithm for nonconvex optimization,

Reference 48

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.400475Z digest=sha256:ea62e5da6d8e4387c1109066b147d22bf60d1be4c83c3bb2d7d615e570b74324

Observation 548c0008-4c01-4100-86a8-99198f92d062 · outbound

This paper cites Adaptive switching circuits,.

Stability of first-order methods in tame optimization Adaptive switching circuits,

Reference 49

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.404343Z digest=sha256:d7ea87482cf7c6f565d9bb4d5d97dae76a13e9c361ad9488c9fe1239b9f94790

Observation 3e2d3ecd-907e-4407-8245-5f2feb281c0f · outbound

This paper cites An adaptive associative memory principle,.

Stability of first-order methods in tame optimization An adaptive associative memory principle,

Reference 50

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source=pdf_text observed=2026-08-12T05:16:51.408391Z digest=sha256:4778e118b85f20237f33915f91a90401053afadcc73a7a2d9d7bda0e8f6b8ec5

Observation 9cc9c2c8-e1b7-4233-a943-26050beb3053 · outbound

This paper cites On the convergence of the lms algorithm with adaptive learning rate for linear feedforward networks,.

Stability of first-order methods in tame optimization On the convergence of the lms algorithm with adaptive learning rate for linear feedforward networks,

Reference 51

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.412414Z digest=sha256:b60a455c0c37021a8cfb35742c8a544f00d10fdc355db73c04f7c524f6c99036

Observation ab4c409b-bde4-42fe-a8e3-57ad00ccc6b5 · outbound

This paper cites Incremental subgradient methods for nondifferentiable op- timization,.

Stability of first-order methods in tame optimization Incremental subgradient methods for nondifferentiable op- timization,

Reference 52

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.783361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.416492Z digest=sha256:0099acdebe98dba7eeb1ab180801f0af025e73fad5bad037ed8a3e3f6fa7f849

Observation 34bccf6f-d277-4bb3-a5d8-08365965e127 · outbound

This paper cites Incremental gradient, subgradient, and proximal methods for convex optimization: A survey,.

Stability of first-order methods in tame optimization Incremental gradient, subgradient, and proximal methods for convex optimization: A survey,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.770022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.420722Z digest=sha256:56551147d5ca5ff4a21180830f3644dc9558b9a2fa9a9eb4af74583d90666c95

Observation 03213abb-66cf-462a-9daa-e647449597de · outbound

This paper cites Why random reshuffling beats stochas- tic gradient descent,.

Stability of first-order methods in tame optimization Why random reshuffling beats stochas- tic gradient descent,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.756710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.424868Z digest=sha256:ac2bb70f4792b31cf00168759a064ff4be17f661a3bc37953e89460378665a59

Observation e0752615-e712-4016-b399-e8a7670b8e44 · outbound

This paper cites Random reshuffling: Simple analysis with vast improvements,.

Stability of first-order methods in tame optimization Random reshuffling: Simple analysis with vast improvements,

Reference 55

Resolution
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raw_fallback, observed 2026-08-12T05:16:52.744034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.429666Z digest=sha256:d689704b0c73d084dc8f29688c646ed0ad987c7a386c393a665f34a8a5b2e8e1

Observation d7394bbf-1201-4da1-b651-f9a58ef4b1a2 · outbound

This paper cites A unified convergence analysis for shuffling-type gradient methods,.

Stability of first-order methods in tame optimization A unified convergence analysis for shuffling-type gradient methods,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.730757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.434017Z digest=sha256:b3136f63a5e40dec4b1f62c2e640dd4db7bb8e4318b90a0861cfdd0e09666cf7

Observation 3bbb68e2-8ada-49ba-a1bf-7c3cb38a5024 · outbound

This paper cites Incremental without replacement sampling in nonconvex optimization,.

Stability of first-order methods in tame optimization Incremental without replacement sampling in nonconvex optimization,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.717673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.438257Z digest=sha256:86a1fe2453f92beef13532b5f2346074deb81c056b9276510b944e0d068ce037

Observation 26378519-a92e-4eb8-9183-fc29caefc2c5 · outbound

This paper cites Convergence of random reshuffling under the kurdyka– łojasiewicz inequality,.

Stability of first-order methods in tame optimization Convergence of random reshuffling under the kurdyka– łojasiewicz inequality,

Reference 58

Resolution
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raw_fallback, observed 2026-08-12T05:16:52.703477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.442080Z digest=sha256:2181884e07b4cc2659d3e2c9b09f3e5d169703bcc7bf98e00adcaf69a7d4f7ce

Observation d9df9354-bfd2-4adb-bfa1-4bab71707da7 · outbound

This paper cites On the importance of initialization and momentum in deep learning,.

Stability of first-order methods in tame optimization On the importance of initialization and momentum in deep learning,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.688758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.446635Z digest=sha256:a5d9b4652349217c651cc6af8963483784ab18fcf243cf86b7b452d2c0de882b

Observation 75cb68f0-a135-462a-9a98-caf37fe6db32 · outbound

This paper cites Smg: A shuffling gradient-based method with momentum,.

Stability of first-order methods in tame optimization Smg: A shuffling gradient-based method with momentum,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.675207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.451803Z digest=sha256:5271cb35235f390c68ca7c8810f25d2703c34e855e23c07d132e22b27b0cb560

Observation cc11de64-e0c3-4517-ae2c-03607392b732 · outbound

This paper cites Nesterov accelerated shuffling gradi- ent method for convex optimization,.

Stability of first-order methods in tame optimization Nesterov accelerated shuffling gradi- ent method for convex optimization,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.660715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.455588Z digest=sha256:f061e231662b5cf5337138ac46dd98fe67b77c9a6937483dd1fc8186df303ef9

Observation 26b2e51a-86ea-4ff9-9480-969112904ec7 · outbound

This paper cites Coordinate descent algorithms,.

Stability of first-order methods in tame optimization Coordinate descent algorithms,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.648016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.459541Z digest=sha256:fa6b7e4b1b30b2a43b58b16446a90718ab73e7d25d2db05c1000c87d6498bbcc

Observation b22dffe7-49a9-46bc-a16d-e5e1b052b7a2 · outbound

This paper cites an unresolved cited work.

Stability of first-order methods in tame optimization Unresolved cited work

Reference 63

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unresolved
raw_fallback, observed 2026-08-12T05:16:52.635925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.464335Z digest=sha256:a6978ea163f89a45b722daaece901c663886d3eb96ee9e7c85eb76310b1ac6ab

Observation a033e2d7-f5e8-492b-9279-a947915cd8ec · outbound

This paper cites On the convergence of the coordinate descent method for convex differentiable minimization,.

Stability of first-order methods in tame optimization On the convergence of the coordinate descent method for convex differentiable minimization,

Reference 64

Resolution
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raw_fallback, observed 2026-08-12T05:16:52.623479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.468188Z digest=sha256:a67b769d81c61eca4c9cb139cb76bca0a33e233dcf10249a4280bf47ad1bcdaf

Observation f4e401ee-4b6a-4cd5-bd6c-9bca75b94be9 · outbound

This paper cites Efficiency of coordinate descent methods on huge-scale optimization prob- lems,.

Stability of first-order methods in tame optimization Efficiency of coordinate descent methods on huge-scale optimization prob- lems,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.611539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.472352Z digest=sha256:fb961d4cba89aade721044e12f3d7c8c3194febaf64834eadd505db799ffc194

Observation 99a53ffb-f590-42ef-810b-a5139fc34e8f · outbound

This paper cites Randomness and per- mutations in coordinate descent methods,.

Stability of first-order methods in tame optimization Randomness and per- mutations in coordinate descent methods,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.598895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.476349Z digest=sha256:a31f0b867204ca1f4f241c78eedd262994fc4fac9727e2bd5db5e81ab1daa583

Observation 64bb4810-13b5-4867-8301-63d4df30f919 · outbound

This paper cites On the convergence of block coordinate descent type meth- ods,.

Stability of first-order methods in tame optimization On the convergence of block coordinate descent type meth- ods,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.585422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.480626Z digest=sha256:fcd7b6b9edda2aed0f53f9bcab6a27c82b1ea93043d855fd560b9c447b4515c7

Observation d0c95008-0ae3-4afb-8d4e-bdaab0c619f4 · outbound

This paper cites Random permutations fix a worst case for cyclic coordinate descent,.

Stability of first-order methods in tame optimization Random permutations fix a worst case for cyclic coordinate descent,

Reference 68

Resolution
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raw_fallback, observed 2026-08-12T05:16:52.571651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.484519Z digest=sha256:9f8f30bdaeef32e2add84bb445d1f954007ef8420bc3459c19c5917f7b741d85

Observation ecfd80f7-e3d6-4aa7-9567-4b88545d7ac3 · outbound

This paper cites Euler, Institutiones calculi integralis.

Stability of first-order methods in tame optimization Euler, Institutiones calculi integralis

Reference 69

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.557217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.488124Z digest=sha256:785910e5463e1365cb684f69d24a0ad2d2fa8fa38186687fed9ddf80dcba39ca

Observation 15bf9183-b95b-4d1d-bb99-52d2312744b7 · outbound

This paper cites Blanton, Foundations of Differential Calculus.

Stability of first-order methods in tame optimization Blanton, Foundations of Differential Calculus

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.543294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.492744Z digest=sha256:bd5eeb16a8ee8c4b9e934569b2ae1cf63c5d4118d2fbb1358eca025d917b79ad

Observation 03ccd5b5-0f87-4fb9-915d-b611fc0007b1 · outbound

This paper cites an unresolved cited work.

Stability of first-order methods in tame optimization Unresolved cited work

Reference 71

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unresolved
raw_fallback, observed 2026-08-12T05:16:52.530348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.496494Z digest=sha256:aed27bb5135357c118c85c4befe0501e20dae3f922725f2f986599a7040f1942

Observation 108a98fe-153f-4884-80d6-8e042783788c · outbound

This paper cites Analysis of recursive stochastic algorithms,.

Stability of first-order methods in tame optimization Analysis of recursive stochastic algorithms,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.515805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.500912Z digest=sha256:73cc2aa35032e078b5bb471c0b4f3cd93e45a5b5750a13fc8a45141467eedaa5

Observation 8bf377a1-275a-4260-b088-25119eb26aa1 · outbound

This paper cites General convergence results for stochastic approximations via weak con- vergence theory,.

Stability of first-order methods in tame optimization General convergence results for stochastic approximations via weak con- vergence theory,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.500949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.505584Z digest=sha256:3af72a95647b1ada6132ba1247e2d3991cfe6f543cb124e28da4791a1a296a6a

Observation 3b50eef9-e457-45b1-b373-e82dc28ab35e · outbound

This paper cites Convergence of recursive adaptive and identification procedures via weak convergence theory,.

Stability of first-order methods in tame optimization Convergence of recursive adaptive and identification procedures via weak convergence theory,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.488368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.509569Z digest=sha256:5566dc58fb041a0476cbfa3e450eea35ba06ef3a48ffa48cfb1fd7aa37d45303

Observation 7e38ce05-1188-44ef-9974-53dbe10c003c · outbound

This paper cites Stochastic approximations and differential inclu- sions,.

Stability of first-order methods in tame optimization Stochastic approximations and differential inclu- sions,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.474584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.513574Z digest=sha256:d132ccbb498bec7bdda213fdcd4c75791f33d0a8f86a9ebece06c5e01ebfb8c1

Observation 59138bed-64d9-4829-b95e-47c1609c4efd · outbound

This paper cites Stochastic approximations and differential inclu- sions, part ii: Applications,.

Stability of first-order methods in tame optimization Stochastic approximations and differential inclu- sions, part ii: Applications,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.461670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.517914Z digest=sha256:093bc71ce70438456a088a8a99f3db74fb8713209356a976667bb0b2bc812201

Observation 1a7cbc52-e390-4965-8cbd-8c5b814fa7eb · outbound

This paper cites Dynamics of stochastic approximation algorithms,.

Stability of first-order methods in tame optimization Dynamics of stochastic approximation algorithms,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.447968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.521920Z digest=sha256:46bef67f25ef305f27199ac984af245df67649350fec309cf1d7ee89cae10b06

Observation 557c7be8-ec6c-4e78-b819-4c0e0ee09115 · outbound

This paper cites an unresolved cited work.

Stability of first-order methods in tame optimization Unresolved cited work

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-12T05:16:51.525669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.525669Z digest=sha256:98cfccaebffea75264b57b55e803e002802caef7629d19142778a86df724f437

Observation 203578d7-d059-4124-8971-5bc6158153f7 · outbound

This paper cites Stochastic methods for composite and weakly convex optimiza- tion problems,.

Stability of first-order methods in tame optimization Stochastic methods for composite and weakly convex optimiza- tion problems,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.426792Z

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source=pdf_text observed=2026-08-12T05:16:51.529511Z digest=sha256:bc9179bf07e08ecc2d84878b17793b67dc81e0b6b01789e9ff9c896ed72e2321

Observation f1509e88-a81a-4538-804c-259868866651 · outbound

This paper cites Conservative set valued fields, automatic differentiation, stochas- tic gradient methods and deep learning,.

Stability of first-order methods in tame optimization Conservative set valued fields, automatic differentiation, stochas- tic gradient methods and deep learning,

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.411712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.533377Z digest=sha256:2bddc10e6186face53995fccaa9e7f7463b0f07ffc22dcc3247a33e7d61aeaf3

Observation 5ae65100-fd7c-44e5-b7c6-c6a0abcb0099 · outbound

This paper cites Random monotone operators and application to stochastic optimization,.

Stability of first-order methods in tame optimization Random monotone operators and application to stochastic optimization,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.398569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.537241Z digest=sha256:e49dce4cede3b4011daf7f825b090265bddef86907082bb5e1abbe7728cc215c

Observation d61b1c1d-086d-4b00-b916-22df139f6527 · outbound

This paper cites Adam-family methods for nonsmooth optimiza- tion with convergence guarantees,.

Stability of first-order methods in tame optimization Adam-family methods for nonsmooth optimiza- tion with convergence guarantees,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.385015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.541127Z digest=sha256:04bb1cf1b432fcaca4b86a1492086aed5e1518b8e315726b13d3be466c1dcc8f

Observation fc8e26db-f23d-4a13-8222-3a08e52bc7c6 · outbound

This paper cites Global stability of first-order methods for coercive tame functions,.

Stability of first-order methods in tame optimization Global stability of first-order methods for coercive tame functions,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.370272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.544823Z digest=sha256:51e5ce952f8e77a039c1307507e57bb044afc7e1035e61b4cca5ea5210707802

Observation 9afd5c15-5abc-44fb-aa51-55b585b8ef21 · outbound

This paper cites Converging multistep methods for initial value problems involving multival- ued maps,.

Stability of first-order methods in tame optimization Converging multistep methods for initial value problems involving multival- ued maps,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.357041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.548833Z digest=sha256:346193c2aadc82c3ac2eb8c486f5ba2132bdb4cb9202cec61540b21a8a479719

Observation 152df49c-cc30-4820-87a7-d6e75d19754f · outbound

This paper cites an unresolved cited work.

Stability of first-order methods in tame optimization Unresolved cited work

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-12T05:16:51.552713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.552713Z digest=sha256:93f1bd6df59c2d9091b3d5f4e2cdb4f15c42ebb4f5d75024af18f997912d66e0

Observation 1c1d6405-3fc7-4e64-bc4d-240aa15a5c81 · outbound

This paper cites Difference methods for differential inclusions: A survey,.

Stability of first-order methods in tame optimization Difference methods for differential inclusions: A survey,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.335758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.557092Z digest=sha256:3572cd53490c147c97b9779fd2845a10a01d2b89e986859c532ee4a0d1504f1c

Observation 97fffbd4-23d8-46db-880b-e1ee78d5d189 · outbound

This paper cites Subgradient methods for sharp weakly convex functions,.

Stability of first-order methods in tame optimization Subgradient methods for sharp weakly convex functions,

Reference 87

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.321997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.561198Z digest=sha256:65cf19165b6365e6fd95165aab2361761dd0ece1a925feaf6e0ebd6c1b2df415

Observation 9419fa9c-b992-4c3a-b35d-359ed505e719 · outbound

This paper cites Stochastic algorithms with geometric step decay converge linearly on sharp functions.

Stability of first-order methods in tame optimization Stochastic algorithms with geometric step decay converge linearly on sharp functions

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-12T05:16:51.565603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:51.565603Z digest=sha256:1120af4fc656bde54b65bfcf036f0475cefba89ba8c638ce89fd7e17ec9d1d6d

Observation 26d2bdc3-07dc-4a23-a5f7-43c65b0f89b1 · outbound

This paper cites Low-rank matrix recovery with composite optimization: Good conditioning and rapid convergence,.

Stability of first-order methods in tame optimization Low-rank matrix recovery with composite optimization: Good conditioning and rapid convergence,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.307778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.570033Z digest=sha256:d6ecf573c627c8a27e02ed0a64586cae93efab6b7b3286537532c719d4b08b22

Observation b986769d-3694-48bb-b65c-f1bca667af78 · outbound

This paper cites On the stable equilibrium points of gradient systems,.

Stability of first-order methods in tame optimization On the stable equilibrium points of gradient systems,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.294794Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T05:16:51.573677Z digest=sha256:9cf80923577aab5341c6de89f0ce3afc5a1d73e929ac9db07b0f2e3e4a4eca1d

Observation 34ad5a8e-4c8f-462e-a909-864e4eabdb75 · outbound

This paper cites Favorable classes of lipschitz continuous functions in subgradient opti- mization,.

Stability of first-order methods in tame optimization Favorable classes of lipschitz continuous functions in subgradient opti- mization,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.282704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.578345Z digest=sha256:53525d4dd8f2f41dc811af5f48d48688e88f810217f76766041b1b783e14ccf0

Observation f6ab1e0e-9687-4416-b42b-4be5e1562c96 · outbound

This paper cites Generic differentiability of lipschitzian functions,.

Stability of first-order methods in tame optimization Generic differentiability of lipschitzian functions,

Reference 92

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.270680Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T05:16:51.582464Z digest=sha256:27028666114689d83511afa45d95201710dbc66be3187cdd7506e9b3ebbb6fe8

Observation ab375fe1-0222-42cd-9081-177a62a43f99 · outbound

This paper cites Convergence of the iterates of descent methods for analytic cost functions,.

Stability of first-order methods in tame optimization Convergence of the iterates of descent methods for analytic cost functions,

Reference 93

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.257876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.586493Z digest=sha256:0b44c9293e4ba7fa57a88bbe441ae0dd7565c8a1bd06140a2c5b4f1e5941058c

Observation 0f0a5b31-ff8f-4cce-9784-158a246934e7 · outbound

This paper cites Abadi et al.

Stability of first-order methods in tame optimization Abadi et al

Reference 94

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.244737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.590443Z digest=sha256:a88c935de17f078b48ffcba05f2494238636bc77c527cc2c17ba0cc3d18f7cbd

Observation 46348cf6-6adc-4282-a49d-515336733d57 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Stability of first-order methods in tame optimization Pytorch: An imperative style, high-performance deep learning library,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.230859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.594666Z digest=sha256:fc32ebb12f69e6fad9684ab674e450e832e5a23d6125485e8b2c67374bcc101e

Observation ff5cf138-5746-49b1-adbf-0754d51c379e · outbound

This paper cites A simple weight decay can improve generalization,.

Stability of first-order methods in tame optimization A simple weight decay can improve generalization,

Reference 96

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.216737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.598653Z digest=sha256:823044233aca3fc9e550e43a81b3fab4ad87bb506604d07e92b02cf3ef82ae00

Observation cc54ec23-6046-4d70-9b4c-37e1e2885a6b · outbound

This paper cites Regression shrinkage and selection via the lasso,.

Stability of first-order methods in tame optimization Regression shrinkage and selection via the lasso,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.201723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.602958Z digest=sha256:451c9399ac21a8cfa3171a3b27012ce79a8f8a957beb43306a32fd8bb1179454

Observation bc081d89-66ae-4624-8e1a-2f01495fc42e · outbound

This paper cites Matrix Completion has No Spurious Local Minimum,.

Stability of first-order methods in tame optimization Matrix Completion has No Spurious Local Minimum,

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.188076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.607696Z digest=sha256:8e270de3b0c3192a92ee66c96079b40d3961fad233607073e00aad230964e749

Observation bcc4f8ca-460b-491a-934d-1792aaebaba8 · outbound

This paper cites Beck, First-order methods in optimization.

Stability of first-order methods in tame optimization Beck, First-order methods in optimization

Reference 99

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verified fuzzy
raw_fallback, observed 2026-08-12T05:16:52.176160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.611688Z digest=sha256:f36062b7e43da04665909c0e76171f51a62859295c97cfa0126bc7980ac92ef8

Observation 5f52bec6-236f-4ec4-9cf3-29fd2bcb42a0 · outbound

This paper cites an unresolved cited work.

Stability of first-order methods in tame optimization Unresolved cited work

Reference 100

Resolution
unresolved
raw_fallback, observed 2026-08-12T05:16:52.163537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T05:16:51.615837Z digest=sha256:97535ed1bc7a440c1db1fa58b2759b213bea47f7e7b0ace91f9bed9a158f36c9

Pith citing papers

No inbound Pith citation observations are available.