Paper Citation Record · LEDGER

ID3 Learns Juntas for Smoothed Product Distributions

As of 6 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:1906.08654.

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

pith.paper-citation-record.v1
1906.08654 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T19:41:47.309669Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

34 of 34 outbound references displayed

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verified fuzzy21
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8b94b1a-2399-4bbf-b2b8-d60b81b73834 · outbound

This paper cites Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers.

ID3 Learns Juntas for Smoothed Product Distributions Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-25T19:46:10.524339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4b55879c-9299-47e0-b390-ab15d01bd879 · outbound

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

ID3 Learns Juntas for Smoothed Product Distributions A Convergence Theory for Deep Learning via Over-Parameterization

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.499539Z

Source-reported events for the cited work

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Observation 0cafec1a-4a76-4191-8fb9-8a1cd0f0c1d9 · outbound

This paper cites Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks.

ID3 Learns Juntas for Smoothed Product Distributions Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.511051Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6ef7d665-d658-4af8-88d0-ea6246f622ea · outbound

This paper cites Rank-r decision trees are a subclass of r-dec ision lists.

ID3 Learns Juntas for Smoothed Product Distributions Rank-r decision trees are a subclass of r-dec ision lists

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.335220Z

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Observation 52ca0074-c4b1-485d-b13c-16e660d49f42 · outbound

This paper cites Weakly learning dnf and characterizing statistical query learning using fourier analysis.

ID3 Learns Juntas for Smoothed Product Distributions Weakly learning dnf and characterizing statistical query learning using fourier analysis

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.311384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation df6fdcad-c9bd-495a-a264-2663893e45c3 · outbound

This paper cites Noise-tolera nt learning, the parity problem, and the statistical query model.

ID3 Learns Juntas for Smoothed Product Distributions Noise-tolera nt learning, the parity problem, and the statistical query model

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.305293Z

Source-reported events for the cited work

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Observation fd65e0bd-7e58-4025-b00d-769b11c64702 · outbound

This paper cites SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data.

ID3 Learns Juntas for Smoothed Product Distributions SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.517807Z

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Observation 44df274c-b8f9-4b29-956f-ec7dffa7c0e5 · outbound

This paper cites On the proper learnin g of axis-parallel concepts.

ID3 Learns Juntas for Smoothed Product Distributions On the proper learnin g of axis-parallel concepts

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.330539Z

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Observation 551c350b-dd83-4b69-aef4-c3cc2e9c6635 · outbound

This paper cites On using extended sta tistical queries to avoid member- ship queries.

ID3 Learns Juntas for Smoothed Product Distributions On using extended sta tistical queries to avoid member- ship queries

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.316389Z

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Observation 0933d055-f77a-4603-ae4d-78d20f54a30d · outbound

This paper cites Learning dnf from random walks.

ID3 Learns Juntas for Smoothed Product Distributions Learning dnf from random walks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.325898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 090a1293-39be-49a6-95cb-7b051bfaec69 · outbound

This paper cites Beyond the Low-Degree Algorithm: Mixtures of Subcubes and Their Applications.

ID3 Learns Juntas for Smoothed Product Distributions Beyond the Low-Degree Algorithm: Mixtures of Subcubes and Their Applications

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.505495Z

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Observation e6689616-ba50-4f5a-b6aa-4f2f106ccfd4 · outbound

This paper cites Sgd learns the conjugate kernel class of t he network.

ID3 Learns Juntas for Smoothed Product Distributions Sgd learns the conjugate kernel class of t he network

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.297050Z

Source-reported events for the cited work

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Observation 507705b1-a834-4a09-b5f9-84563c5a3d50 · outbound

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

ID3 Learns Juntas for Smoothed Product Distributions Gradient Descent Provably Optimizes Over-parameterized Neural Networks

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.530447Z

Source-reported events for the cited work

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Observation 507fc251-3184-4b88-b5e5-e22c632bc64d · outbound

This paper cites Learning deci sion trees from random examples.

ID3 Learns Juntas for Smoothed Product Distributions Learning deci sion trees from random examples

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.320699Z

Source-reported events for the cited work

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Observation 5646b298-5994-466c-947d-783271740b16 · outbound

This paper cites New results for learning noisy parities and halfspaces.

ID3 Learns Juntas for Smoothed Product Distributions New results for learning noisy parities and halfspaces

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.300933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ac1b1bc6-9e03-41a8-ae27-113cbf874040 · outbound

This paper cites On agnos- tic learning of parities, monomials, and halfspaces.

ID3 Learns Juntas for Smoothed Product Distributions On agnos- tic learning of parities, monomials, and halfspaces

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.367770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c4c32737-34c7-4001-9fc2-deb5a92be012 · outbound

This paper cites Decision trees: More the oretical justiﬁcation for practical algorithms.

ID3 Learns Juntas for Smoothed Product Distributions Decision trees: More the oretical justiﬁcation for practical algorithms

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.360104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7f4747ad-f2ae-450c-ad3b-cfcb8c3b7265 · outbound

This paper cites Hyperparameter Optimization: A Spectral Approach.

ID3 Learns Juntas for Smoothed Product Distributions Hyperparameter Optimization: A Spectral Approach

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.459811Z

Source-reported events for the cited work

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Observation 11ef6297-fa51-40b9-a159-9f0349ef7388 · outbound

This paper cites Learning random log-depth decision trees under the uniform distribution.

ID3 Learns Juntas for Smoothed Product Distributions Learning random log-depth decision trees under the uniform distribution

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.348229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 74f0ff1c-5d3a-4998-8727-872fe0b2f03c · outbound

This paper cites Decision trees are PAC-learnable from most product distributions: a smoothed analysis.

ID3 Learns Juntas for Smoothed Product Distributions Decision trees are PAC-learnable from most product distributions: a smoothed analysis

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.479801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation df1bd29f-1785-49f9-934a-e5f7e1d9a601 · outbound

This paper cites Boosting theory towards practice: Rec ent developments in decision tree induction and the weak learning framework.

ID3 Learns Juntas for Smoothed Product Distributions Boosting theory towards practice: Rec ent developments in decision tree induction and the weak learning framework

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.339793Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a43360c0-74de-4979-9863-2a3fabf0c96f · outbound

This paper cites On the boosting abil ity of top–down decision tree learn- ing algorithms.

ID3 Learns Juntas for Smoothed Product Distributions On the boosting abil ity of top–down decision tree learn- ing algorithms

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.381507Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cd02752f-6e27-4956-8dbc-d78c7ce590a1 · outbound

This paper cites Learning decisio n trees using the fourier spectrum.

ID3 Learns Juntas for Smoothed Product Distributions Learning decisio n trees using the fourier spectrum

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.376112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 594230e1-80ae-49d6-b302-f918a27c482b · outbound

This paper cites Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent.

ID3 Learns Juntas for Smoothed Product Distributions Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-25T19:46:10.453628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 393b31fb-dcfb-4168-b006-3d3e92fc1cc3 · outbound

This paper cites A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics.

ID3 Learns Juntas for Smoothed Product Distributions A Comparative Analysis of the Optimization and Generalization Property of Two-layer Neural Network and Random Feature Models Under Gradient Descent Dynamics

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-25T19:46:10.467554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1081f446-24fd-4850-a4bf-239520346a4c · outbound

This paper cites Learning monotone decision trees in polynomial time.

ID3 Learns Juntas for Smoothed Product Distributions Learning monotone decision trees in polynomial time

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.344001Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8727ee5b-263c-4b13-bce0-4f3c795d3377 · outbound

This paper cites Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?.

ID3 Learns Juntas for Smoothed Product Distributions Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.493693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fb16fe27-e7b2-4461-bb61-9f288190f651 · outbound

This paper cites Towards moderate overparameterization: global convergence guarantees for training shallow neural networks.

ID3 Learns Juntas for Smoothed Product Distributions Towards moderate overparameterization: global convergence guarantees for training shallow neural networks

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.487440Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4cd1ceb6-f815-4ce8-8550-bbdb8ab888b6 · outbound

This paper cites Ross Quinlan.

ID3 Learns Juntas for Smoothed Product Distributions Ross Quinlan

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.355837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c44c4c14-a8cc-472b-b825-3540172b0cb9 · outbound

This paper cites Learning decision lists.

ID3 Learns Juntas for Smoothed Product Distributions Learning decision lists

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.363900Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c9e3c00c-bd33-4a73-9ce7-084fed329540 · outbound

This paper cites Understanding machine learning: From theory to algorithms.

ID3 Learns Juntas for Smoothed Product Distributions Understanding machine learning: From theory to algorithms

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.371854Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e517468b-1eae-40ca-b7dd-4d83e9fa88b5 · outbound

This paper cites Failures of gradient-based deep learning.

ID3 Learns Juntas for Smoothed Product Distributions Failures of gradient-based deep learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.385699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 85c3ecc2-15b4-4025-af32-b174c8de58c2 · outbound

This paper cites Smoothed analysi s of algorithms: Why the simplex algorithm usually takes polynomial time.

ID3 Learns Juntas for Smoothed Product Distributions Smoothed analysi s of algorithms: Why the simplex algorithm usually takes polynomial time

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T19:47:08.351954Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ac63bc3b-f7d8-42be-9770-ef7b6f2e13d7 · outbound

This paper cites Diverse Neural Network Learns True Target Functions.

ID3 Learns Juntas for Smoothed Product Distributions Diverse Neural Network Learns True Target Functions

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-05-25T19:46:10.474440Z

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No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

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