Pith. sign in

Paper Citation Record · LEDGER

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression

As of 11 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2501.13790.

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

pith.paper-citation-record.v1
2501.13790 v2

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:46:47.779439Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

47 of 47 outbound references displayed

  • verified exact1
  • verified fuzzy27
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a37cd258-0359-4903-94ac-22a3b6a7f09f · outbound

This paper cites Communication complexity of distributed convex learning and optimization.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Communication complexity of distributed convex learning and optimization

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.497755Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.547875Z digest=sha256:01aac56bd05b030a757cc6a54e298d0f1936a02b826087063b0c20147039e93b

Observation 14e2327a-b59b-46a0-a82d-b70593fb9fc1 · outbound

This paper cites Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.481154Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.553915Z digest=sha256:fcca0b750705cd84e757fee97aec63b5f0a50fc346aac1eeec1dcc4d149baebf

Observation 7995ca07-4999-47ab-9ebe-20f901db577e · outbound

This paper cites Distributed learning, communication complexity and privacy.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Distributed learning, communication complexity and privacy

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.465943Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.559373Z digest=sha256:590d620b3a7a0b4fc82ae8e47ad6e3a9161a335f33f174ebcc35e5eae5bfb1fd

Observation c6b5e213-be08-4ffe-ace2-cf483f29e582 · outbound

This paper cites Gradient descent on neural networks typically occurs at the edge of stability.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Gradient descent on neural networks typically occurs at the edge of stability

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.448354Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.566003Z digest=sha256:adecbc187ce01b9a2857166632935b33f839dde013e2124b05f6c6fa754213ed

Observation 5f460f20-dc5c-4b94-8209-12d2be8c0ff0 · outbound

This paper cites Optimal distributed online prediction using mini-batches.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Optimal distributed online prediction using mini-batches

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.433228Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.571559Z digest=sha256:36cc5b4e7bd8b872bad89628c82b579e92a0bff86151f900571af6d34403decd

Observation 1464e2d9-3b0d-4262-9578-506d6912199c · outbound

This paper cites Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization i: A generic algorithmic framework.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization i: A generic algorithmic framework

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.576742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.576742Z digest=sha256:67b29f5f9306c62b4b52dd45ac1abbb01dad5863b583e6c35bcbf3b309939680

Observation 72110b65-9ec8-4a0b-8045-b9ec7801e4ee · outbound

This paper cites Sharp bounds for federated averaging (local sgd) and continuous perspective.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Sharp bounds for federated averaging (local sgd) and continuous perspective

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.407281Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.582207Z digest=sha256:d637dac716e8a59a14191c071f8d61aa86fa8e51d4d31aeea8a99517c2d5969b

Observation 9775e904-e1c6-49cf-933b-fa760af9f3db · outbound

This paper cites Characterizing implicit bias in terms of optimization geometry.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Characterizing implicit bias in terms of optimization geometry

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.390148Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.587445Z digest=sha256:d8e8d13b97eb99b13e27d0c27d8eff07a592340d354bc83b07c999363c228982

Observation 5735e215-e8a2-4bc7-b6c9-ab02ee3637a4 · outbound

This paper cites On the Convergence of Local Descent Methods in Federated Learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression On the Convergence of Local Descent Methods in Federated Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.592529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.592529Z digest=sha256:2d573d1b0a061552e6958fa6a1a484f6e6362af117786d0e775b859f1a24213f

Observation f899152c-e320-4cce-96d6-28bf9fec06b1 · outbound

This paper cites Deep residual learning for image recognition.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Deep residual learning for image recognition

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.598119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.598119Z digest=sha256:86bbbefd0edbf900f5e1a7ec9e50074470b1a4413dcc42521d9822cd3f97000c

Observation b2c9ffab-6320-4584-a086-e916b71a501e · outbound

This paper cites Risk and parameter convergence of logistic regression.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Risk and parameter convergence of logistic regression

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.602767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.602767Z digest=sha256:d15a0c0847b755d754fc7d369801b23737164565047d32c8d8d2255bf49b7a26

Observation 242c0e72-40cd-49f0-a785-47ef71b66b3e · outbound

This paper cites Fast margin maximization via dual acceleration.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Fast margin maximization via dual acceleration

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.365136Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.607982Z digest=sha256:1aa3a00beeb073076b803f2598a9b82fac51e0ed140d89ecdf51c6b6aaa6c9aa

Observation 3a99c2c4-1754-4a19-adb6-94d178ce570e · outbound

This paper cites Advances and Open Problems in Federated Learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Advances and Open Problems in Federated Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.612502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.612502Z digest=sha256:5ffb2b01f1804e3c227e4d322720c1651708c644d6a2418d201c5eead8f4d5d0

Observation 6b6cf274-2572-496d-bf60-7e666961a3d0 · outbound

This paper cites Advances and open problems in federated learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Advances and open problems in federated learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.617690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.617690Z digest=sha256:4919fd3a5c2f372cffa6b855cf2c15baba0caec4d58985e1d2e4743b90e25151

Observation 69e8a5cd-4fa6-47a3-a9fc-f8fb23fe347d · outbound

This paper cites Scaffold: Stochastic controlled averaging for federated learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Scaffold: Stochastic controlled averaging for federated learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.622481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.622481Z digest=sha256:113b459e5d3d3cfa1865e2f231c1956b7a8b58fe5165b5a94bf297060b0cb49c

Observation 8ac92962-002d-49d2-8b24-a9656cc158c8 · outbound

This paper cites Tighter theory for local sgd on identical and heterogeneous data.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Tighter theory for local sgd on identical and heterogeneous data

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.327498Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.627218Z digest=sha256:94dd0c19369b7f0c6015e89bb65065d0add7cb0b31a2b8293295274cb55c4754

Observation cfcc2ec2-8ecb-48bb-9d7d-a24906acdd30 · outbound

This paper cites A unified theory of decentralized sgd with changing topology and local updates.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression A unified theory of decentralized sgd with changing topology and local updates

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.310600Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.632412Z digest=sha256:0bd4fe2a4e8be78f15edfb92eb65f472fef13245541a271c7676cfee47a05d94

Observation dc729fa8-7f92-4226-a8fc-6e9231dcd9d0 · outbound

This paper cites SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression SLowcal-SGD: Slow Query Points Improve Local-SGD for Stochastic Convex Optimization

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-10T15:46:47.889279Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.637050Z digest=sha256:e088c967d52803e41f304492bff816103a637baa9a984c015e0a7c2d15a4b779

Observation 3f0cec6c-dcf2-4ebd-85d7-d1072a72e2b6 · outbound

This paper cites Don't use large mini-batches, use local sgd.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Don't use large mini-batches, use local sgd

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.295099Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.642171Z digest=sha256:823a3f63bdd3a58fa85cbb4af7778012525272ce8d321bd83c68cc015821d230

Observation aa8eaeea-d511-4d82-bf74-fb571c48af1b · outbound

This paper cites Efficient large-scale distributed training of conditional maximum entropy models.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Efficient large-scale distributed training of conditional maximum entropy models

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.279589Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.647041Z digest=sha256:ab5ca140eee5a89d6c2234ca11a02bfb0e0b03db19bd7f9efc5edb5821df1be9

Observation 96cd270d-3102-41be-a050-7891f00f85a0 · outbound

This paper cites Distributed training strategies for the structured perceptron.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Distributed training strategies for the structured perceptron

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.264210Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.651852Z digest=sha256:791c9010a5e2a0368458f0796e06b997ed5844ad24cac170433a150420fe5f3f

Observation 20ae09e3-7989-40c6-a7e7-f26d405b2170 · outbound

This paper cites Communication-Efficient Learning of Deep Networks from Decentralized Data.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Communication-Efficient Learning of Deep Networks from Decentralized Data

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.656728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.656728Z digest=sha256:47d7c0105654108e1083da9757655b0aa6685cd11b24dca6de4126a99d9bbb36

Observation 64a299ee-01aa-440a-8d6b-69a7f7df0c93 · outbound

This paper cites Proximal and federated random reshuffling.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Proximal and federated random reshuffling

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.239008Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.661732Z digest=sha256:5ff111ad170e73b867b47066a812c97d2e49d9e3f4ce0212dbc14d7971704260

Observation 4ee241fb-8002-4e79-9b36-030cd3ccccd8 · outbound

This paper cites Stochastic gradient descent on separable data: Exact convergence with a fixed learning rate.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Stochastic gradient descent on separable data: Exact convergence with a fixed learning rate

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.222332Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.667587Z digest=sha256:b377aa91d5e51281d8224884ca9e1ee5e2f237b2c24b0237e7876dacf0ee8806

Observation 974679a0-77bd-401d-8225-5c21af772912 · outbound

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

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Introductory lectures on convex optimization: A basic course, volume 87

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.672305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.672305Z digest=sha256:38178c0be00bc32d17e6b9ef5ef55500eda26c8bc1e941d6b71cbd330532b223

Observation bfe2ed56-1f9b-4ae9-9c98-8d512f74c33e · outbound

This paper cites A minimizer far, far away, 2024.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression A minimizer far, far away, 2024

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.196880Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.677037Z digest=sha256:89cddede89644e19c4be48511e7f56bf80c0a9d956b3e96592a47ea124a13251

Observation 25efdabe-0ee7-4f86-9977-fd8b358108a6 · outbound

This paper cites On the still unreasonable effectiveness of federated averaging for heterogeneous distributed learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression On the still unreasonable effectiveness of federated averaging for heterogeneous distributed learning

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.180318Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.682248Z digest=sha256:313a68c0bb2657603c59d81345f2567080c03b8670ca07df15397bb6087f1449

Observation 10bbef97-0329-4b30-b7dc-b2e5323eb478 · outbound

This paper cites The limits and potentials of local sgd for distributed heterogeneous learning with intermittent communication.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression The limits and potentials of local sgd for distributed heterogeneous learning with intermittent communication

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.163374Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.687037Z digest=sha256:13398291a1b8320d048700f4976b045374029376161c130c8cf82cbf08028a87

Observation f9867f78-3f7c-4625-b054-5fa0441dbce3 · outbound

This paper cites Distributed stochastic optimization and learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Distributed stochastic optimization and learning

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.147628Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.691757Z digest=sha256:90ee706adbd53f56c1274367cdb9b639b29ec3f90b1651d9d88c90a8b8ad21f4

Observation 564d3391-36df-4ad6-89ea-b3bdd871161c · outbound

This paper cites The implicit bias of gradient descent on separable data.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression The implicit bias of gradient descent on separable data

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.130857Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.696254Z digest=sha256:f4909050f3576746c0f20fcd08b8b59315d9ee38af88fb009af95198c863c6b1

Observation f323f905-a048-488b-bfd0-aa2ff7383e44 · outbound

This paper cites Local SGD Converges Fast and Communicates Little.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Local SGD Converges Fast and Communicates Little

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.700925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.700925Z digest=sha256:8cbf84e80e6c7aaf2f93b514b700ad1f23b530b1c7e97ac5196d23aaa23c77c2

Observation 464b7f8b-05a1-4998-8e1a-153c4fc2915b · outbound

This paper cites Local sgd converges fast and communicates little.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Local sgd converges fast and communicates little

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.115350Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.705844Z digest=sha256:823edd9c58624e800ad8635075784d3479978db259dbf800e9492ecbbd721699

Observation 7a377e9c-0abb-4518-8895-df6bdfd23892 · outbound

This paper cites A Field Guide to Federated Optimization.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression A Field Guide to Federated Optimization

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.710477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.710477Z digest=sha256:a9dcdeb430d44db2159df2ae146d6fcb427b389a94558ec4bab142adcdbefaa9

Observation 17fcfc90-36da-4d52-a850-ee1730236330 · outbound

This paper cites On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.715859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.715859Z digest=sha256:15d03404e5cf69d7fbb3191cf5e94c548c9090eda9e02e52a4480fdd788d4192

Observation 13d71d0d-e820-4a32-9a49-338c6da5da02 · outbound

This paper cites Is local sgd better than minibatch sgd? In International Conference on Machine Learning, pp.\ 10334--10343.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Is local sgd better than minibatch sgd? In International Conference on Machine Learning, pp.\ 10334--10343

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.098901Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.720585Z digest=sha256:1ce1e4bf3fa411032c1112b615d8ad8d99f0ef73b9df213c1b2c86e14843403c

Observation b1f52b1e-22fb-49fd-973e-1aae0fdfd9cb · outbound

This paper cites Graph oracle models, lower bounds, and gaps for parallel stochastic optimization.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Graph oracle models, lower bounds, and gaps for parallel stochastic optimization

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.726644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.726644Z digest=sha256:103d030cf337a62e5c3ddd0d7b032758d2d5d8d233d53751ccb5db322d874d40

Observation cf8eb43e-7e2d-4ed7-86dc-ce8eec676e01 · outbound

This paper cites Minibatch vs local sgd for heterogeneous distributed learning.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Minibatch vs local sgd for heterogeneous distributed learning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.070822Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.731134Z digest=sha256:eb872b8613fe5cd5a7119268035a92506400ea14196ec450d5cfb39b69a91e0b

Observation 21cd2931-a870-434a-9d94-9675a0976255 · outbound

This paper cites The min-max complexity of distributed stochastic convex optimization with intermittent communication.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression The min-max complexity of distributed stochastic convex optimization with intermittent communication

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.053068Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.735592Z digest=sha256:f04f19dd9d35cd76837b3fe4e907c1374138adc20232c9f3954c40c1dca0a643

Observation 5f3e58ba-060e-4578-9d32-bba7b4217b6c · outbound

This paper cites Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Large Stepsize Gradient Descent for Logistic Loss: Non-Monotonicity of the Loss Improves Optimization Efficiency

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.740292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.740292Z digest=sha256:ac9159634eca04be8dc5e675bbde07de2ca1faa3d06ec24cd1cbd2b7ca8855cf

Observation 77fe3839-79f6-4fc3-afc3-78cd4a5a9f29 · outbound

This paper cites Implicit bias of gradient descent for logistic regression at the edge of stability.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Implicit bias of gradient descent for logistic regression at the edge of stability

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.037192Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.745231Z digest=sha256:16d70bfc8804cde0d44fcabdbadc8540e382d8c4d2cc4cfa5eb04ec211aa7b4a

Observation 52e2efb2-1d9f-4873-bd65-a3dec788e6e9 · outbound

This paper cites Federated accelerated stochastic gradient descent.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Federated accelerated stochastic gradient descent

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.021582Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.749965Z digest=sha256:15a3b1bae51380960c7a7bde7ad0e3f9580abdfdbdd6d20a8a41b8e5a84a42b3

Observation 4b77c0b8-8d0c-4336-8b34-b57cdf1cc861 · outbound

This paper cites Information-theoretic lower bounds for distributed statistical estimation with communication constraints.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Information-theoretic lower bounds for distributed statistical estimation with communication constraints

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T15:46:48.005323Z

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.

source=arxiv_source observed=2026-08-10T15:46:47.754451Z digest=sha256:c73595c14d68a78183d9aca048706756a4af7a3686513fcedb502e083f82ee51

Observation ab1d4959-65a6-4dc9-a913-ee131a5b127e · outbound

This paper cites Parallelized stochastic gradient descent.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Parallelized stochastic gradient descent

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.758944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.758944Z digest=sha256:f0a46e671fd1015726d16a523df610c76ff970ddfc5988c9b548ffc9c07317ce

Observation 2850221d-1a0f-49c3-b126-61a33c5ac142 · outbound

This paper cites write newline.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression write newline

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.764016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.764016Z digest=sha256:9c33bbafcd0b9e978e5bcd88ff96d607feb04234fe5d18d7248185b0282e803d

Observation ab9a25ce-ec6d-44ad-8bbf-1353bd0d166e · outbound

This paper cites @esa (Ref.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression @esa (Ref

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.769809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.769809Z digest=sha256:0b17603c06a168e490c8dced6db92152f5cf15e375ecff35d03ae67c9099bfb7

Observation 9ba25018-7fca-4301-b6f8-80f5a964ad88 · outbound

This paper cites an unresolved cited work.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.774739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.774739Z digest=sha256:40cf13f145792e8375575e51fa77e31a2a5337bd56faec78502746f0fd650e44

Observation c3b30e2b-313e-4239-83d7-e625c6d3e92a · outbound

This paper cites an unresolved cited work.

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T15:46:47.779439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:46:47.779439Z digest=sha256:8509b8dba87448deabfabbc966cdc3c16bed0351423ef5fc812853258d2e444e

Pith citing papers

No inbound Pith citation observations are available.