Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T09:43:14.326705Z
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2510.14074.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T09:43:14.326705Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-02T17:31:02.850791Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T17:37:13.925711Z
46 of 46 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a07eb370-ec60-491e-956b-b025dfccb3b9 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Escaping mediocrity: how two-layer networks learn hard single-index models with SGD.CoRR, 2023
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 98e44c79-1ebd-4d77-b12c-2766efc8ece1 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72a2f395-59a8-4157-8cf2-12836040937b · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Minimax theory for high-dimensional gaussian mixtures with sparse mean separation.Advances in Neural Information Processing Systems, 26, 2013
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18c8ed93-829a-479d-85a1-07b97bd8be7c · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0beadbd3-0bb5-49e5-9407-9e5cde07a855 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Spectrally-normalized margin bounds for neural networks.Advances in neural information processing systems, 30, 2017
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2cdc4722-4599-4f3e-808f-a2b1b33ba480 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Local geometry of high-dimensional mixture models: Effective spectral theory and dynamical transitions.arXiv preprint arXiv:2502.15655, 2025
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d458c512-1236-46e6-ab75-f3dbefd2298e · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Online stochastic gradient descent on non- convex losses from high-dimensional inference.The Journal of Machine Learning Research, 22(1):4788– 4838, 2021
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c4ee186-ed31-44c2-a7a0-65d68e331b73 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent High-dimensional limit theorems for SGD: Effective dynamics and critical scaling
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 592d777b-d2b0-4249-a33a-0d0d9ac6677a · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent On-line learning with a perceptron.Europhysics Letters, 28(7):525, 1994
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae175791-8f25-4d48-9804-25b7baae7430 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Learning by on-line gradient descent
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 911930c8-2506-470c-a881-4429791750c4 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Learning curves for sgd on structured features
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b35ee0d-7fa7-405b-b2e8-ec3fcdda8a1d · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent The high-dimensional asymptotics of first order methods with random data
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7af9c46-eba3-4cfe-b74a-62b2e4f45cda · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Sharp global convergence guarantees for iterative nonconvex optimization with random data.Ann
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 63db4703-0472-4232-87da-2088ce0fb78c · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Achieving optimal clustering in gaussian mixture models with anisotropic covariance structures
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9733b769-f2e7-4184-965f-10bd638991bb · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Hitting the high- dimensional notes: An ode for sgd learning dynamics on glms and multi-index models.Information and Inference: A Journal of the IMA, 13(4):iaae028, 2024
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d2a9513-7772-4d20-9b5c-1b463757b0af · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent High-dimensional limit of one-pass SGD on least squares
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57f81619-5ad7-4279-9022-3b437ceea752 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Smoothing the landscape boosts the signal for sgd: Optimal sample complexity for learning single index models.Advances in Neural Information Processing Systems, 36:752–784, 2023
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ca8ada67-5ec5-4a6e-abcc-8087aa093570 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Universality laws for gaussian mixtures in generalized linear models.Advances in Neural Information Processing Systems, 36, 2024
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 79d8822b-e7d6-4a7b-963f-72e8ef0f720a · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent The benefits of reusing batches for gradient descent in two-layer networks: Breaking the curse of information and leap exponents
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3cac6827-63f8-4bac-9b6e-2246a7db3ada · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent High-dimensional asymptotics of prediction: Ridge regression and classification
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32f67fba-4131-4916-80df-010cb57c48fb · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Rigorous dynamical mean-field theory for stochastic gradient descent methods
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06024813-f1f2-4a30-99df-92033055e1a7 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup.Advances in neural information processing systems, 32, 2019
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c914d719-70ce-4d17-98a2-000d0d772ebe · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent The gaussian equivalence of generative models for learning with shallow neural networks
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ebe60c50-00fb-467d-97f1-a9c1a4b1fb3b · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Modeling the influence of data structure on learning in neural networks: The hidden manifold model.Physical Review X, 10(4):041044, 2020
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c8fafa65-3eec-46e0-80d4-2054cc3e4fa4 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Minimax-optimal covariance projected spectral clustering for high- dimensional nonspherical mixtures.arXiv preprint arXiv:2502.02580, 2025
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5dee034-428e-42b1-af0b-a078d524f833 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Fast margin maximization via dual acceleration
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23e8dfae-b4d7-48fe-913f-740e913dd6aa · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Characterizing the implicit bias via a primal-dual analysis
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 225d8dd0-1a8d-46ae-af0f-116d5d8e0ea7 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Trajectory of mini-batch momentum: batch size saturation and convergence in high dimensions.Advances in Neural Information Processing Systems, 35:36944–36957, 2022
Reference 28
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f6398622-2e8f-4bcd-90c5-c1fd43371e18 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Phase transitions and optimal algorithms in high-dimensional gaussian mixture clustering
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7e71a636-828d-4233-b751-052319f99cae · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Optimality of spectral clustering in the gaussian mixture model.The Annals of Statistics, 49(5):2506–2530, 2021
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation edd76747-7d6b-432f-a13e-91284c25cfb3 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Learning curves of generic features maps for realistic datasets with a teacher-student model
Reference 31
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b0923cf-3f23-402d-97f9-d8ee74acd3c6 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Learning gaussian mixtures with generalized linear models: Precise asymptotics in high- dimensions
Reference 32
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ef4e9f0-f1d2-40cf-bfbf-b4f6e456a810 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent High dimensional classification via regularized and unregularized empirical risk minimization: Precise error and optimal loss.stat, 1050:25, 2020
Reference 33
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94a02753-fd48-422c-b009-0b2c9279c068 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Dynamical mean- field theory for stochastic gradient descent in gaussian mixture classification
Reference 34
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fc4034c-9c7f-46c7-a8a4-fc16225d5a0b · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Convergence of gradient descent on separable data
Reference 35
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94acbf43-863a-41c0-8ade-931efa361d56 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent The full spectrum of deepnet hessians at scale: Dynamics with SGD training and sample size
Reference 36
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5106c7c0-c783-4452-9c28-74467aafc06b · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Homogenization of SGD in high-dimensions: Exact dynamics and generalization properties.Mathematical Programming, pages 1–90, 2024
Reference 37
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3c8c4f7-e21b-4323-a5d8-9169e8675505 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Classifying high-dimensional gaussian mixtures: Where kernel methods fail and neural networks succeed
Reference 38
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f17a1bd-6c00-4098-bbba-d05b57cd5784 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Dynamics of on-line gradient descent learning for multilayer neural networks
Reference 39
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a9f716a-6a39-40f6-b100-620b1cecb8c5 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Exact solution for on-line learning in multilayer neural networks.Physical Review Letters, 74(21):4337, 1995
Reference 40
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d808604-d48f-49d5-b3b7-56d3760c80d1 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Random matrix theory proves that deep learning representations of gan-data behave as gaussian mixtures
Reference 41
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2c46541-cdc7-4cbd-b22a-4d2ac218a089 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent The implicit bias of gradient descent on separable data.Journal of Machine Learning Research, 19(70):1–57, 2018
Reference 42
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2bfc8f03-f74c-426f-b1dd-38207e5af8e4 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Theoretical insights into multiclass classification: A high-dimensional asymptotic view.Advancesin Neural Information Processing Systems, 33:8907–8920, 2020
Reference 43
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Unavailable: canonical work link unavailable.
Observation 308282da-29b1-498b-9f11-00bc0abb34d7 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent High-dimensional probability, volume 47 of Cambridge Series in Statistical and Probabilistic Mathematics
Reference 44
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation beecbc06-f7e0-41f5-8703-868135500140 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent A solvable high-dimensional model of GAN.Advances in Neural Information Processing Systems, 32, 2019
Reference 45
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f4f2410-360e-4d5b-83c9-ba29d89f0567 · outbound
Exact Dynamics of Multi-class Stochastic Gradient Descent Data-dependence of plateau phenomenon in learning with neural network—statistical mechanical analysis.Advancesin Neural Information Processing Systems, 32, 2019
Reference 46
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 21607f55-cac6-4e44-b83d-2fe74efa4909 · inbound
Homogenization of $\ell_2$-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent Exact Dynamics of Multi-class Stochastic Gradient Descent
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.