{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:WRZCPLT6B3CILQBCG3YTLPENIU","short_pith_number":"pith:WRZCPLT6","schema_version":"1.0","canonical_sha256":"b47227ae7e0ec485c02236f135bc8d452be372fb05874598d33f37e949cba1b0","source":{"kind":"arxiv","id":"1809.10678","version":1},"attestation_state":"computed","paper":{"title":"Introducing Noise in Decentralized Training of Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Linara Adilova, Nathalie Paul, Peter Schlicht","submitted_at":"2018-09-27T09:45:38Z","abstract_excerpt":"It has been shown that injecting noise into the neural network weights during the training process leads to a better generalization of the resulting model. Noise injection in the distributed setup is a straightforward technique and it represents a promising approach to improve the locally trained models. We investigate the effects of noise injection into the neural networks during a decentralized training process. We show both theoretically and empirically that noise injection has no positive effect in expectation on linear models, though. However for non-linear neural networks we empirically "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1809.10678","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-09-27T09:45:38Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"4d85cd5214f0d16ebfc957f5a5d64afaf0fe5e37df9124d90cf5ccbcc67ceb24","abstract_canon_sha256":"b60b413217d3cee8ce4fb1e08013eb8f289fea1103fe3d769bf163fa6654e99c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:04:35.286599Z","signature_b64":"g4iBQc7+GWCMjHu0pIYNsTBkchbzVsDhABureC40w9q2hNAH+kt97baGs42MNCiGJ8/sZLt6R7B7Ft4KWA8KCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b47227ae7e0ec485c02236f135bc8d452be372fb05874598d33f37e949cba1b0","last_reissued_at":"2026-05-18T00:04:35.286186Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:04:35.286186Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Introducing Noise in Decentralized Training of Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Linara Adilova, Nathalie Paul, Peter Schlicht","submitted_at":"2018-09-27T09:45:38Z","abstract_excerpt":"It has been shown that injecting noise into the neural network weights during the training process leads to a better generalization of the resulting model. Noise injection in the distributed setup is a straightforward technique and it represents a promising approach to improve the locally trained models. We investigate the effects of noise injection into the neural networks during a decentralized training process. We show both theoretically and empirically that noise injection has no positive effect in expectation on linear models, though. However for non-linear neural networks we empirically "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.10678","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1809.10678","created_at":"2026-05-18T00:04:35.286251+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.10678v1","created_at":"2026-05-18T00:04:35.286251+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.10678","created_at":"2026-05-18T00:04:35.286251+00:00"},{"alias_kind":"pith_short_12","alias_value":"WRZCPLT6B3CI","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_16","alias_value":"WRZCPLT6B3CILQBC","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_8","alias_value":"WRZCPLT6","created_at":"2026-05-18T12:33:01.666342+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU","json":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU.json","graph_json":"https://pith.science/api/pith-number/WRZCPLT6B3CILQBCG3YTLPENIU/graph.json","events_json":"https://pith.science/api/pith-number/WRZCPLT6B3CILQBCG3YTLPENIU/events.json","paper":"https://pith.science/paper/WRZCPLT6"},"agent_actions":{"view_html":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU","download_json":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU.json","view_paper":"https://pith.science/paper/WRZCPLT6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.10678&json=true","fetch_graph":"https://pith.science/api/pith-number/WRZCPLT6B3CILQBCG3YTLPENIU/graph.json","fetch_events":"https://pith.science/api/pith-number/WRZCPLT6B3CILQBCG3YTLPENIU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU/action/storage_attestation","attest_author":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU/action/author_attestation","sign_citation":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU/action/citation_signature","submit_replication":"https://pith.science/pith/WRZCPLT6B3CILQBCG3YTLPENIU/action/replication_record"}},"created_at":"2026-05-18T00:04:35.286251+00:00","updated_at":"2026-05-18T00:04:35.286251+00:00"}