{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:BT56YY2XIYGEGYK7MZRJDFYP7J","short_pith_number":"pith:BT56YY2X","schema_version":"1.0","canonical_sha256":"0cfbec6357460c43615f666291970ffa53f79e3cb64984853bfbb097b39f9e07","source":{"kind":"arxiv","id":"2312.03120","version":1},"attestation_state":"computed","paper":{"title":"The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Joseph Manzano, Kevin Barker, Oceane Bel, Omer Subasi","submitted_at":"2023-12-05T20:40:05Z","abstract_excerpt":"With the advance of the powerful heterogeneous, parallel and distributed computing systems and ever increasing immense amount of data, machine learning has become an indispensable part of cutting-edge technology, scientific research and consumer products. In this study, we present a review of modern machine and deep learning. We provide a high-level overview for the latest advanced machine learning algorithms, applications, and frameworks. Our discussion encompasses parallel distributed learning, deep learning as well as federated learning. As a result, our work serves as an introductory text "},"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":"2312.03120","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-12-05T20:40:05Z","cross_cats_sorted":["cs.AI","cs.DC"],"title_canon_sha256":"194bd12dd622543dd002d5b5833808d671b40afd766f0f6802f4c1253fd2e456","abstract_canon_sha256":"a2efcb9be24f90e12cbdae8920473ae2d5c764a84bf5d0da147c844558b6abb4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:20:58.391733Z","signature_b64":"wMwSeFpSS+eOWRRv+YRIa8ihkkvIIU45j7WwM/I/uV0RLnRwjLTmVC9KMeHRNrvZJs/vYYu4UYjppOIjIcJ8Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0cfbec6357460c43615f666291970ffa53f79e3cb64984853bfbb097b39f9e07","last_reissued_at":"2026-07-05T07:20:58.391280Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:20:58.391280Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.DC"],"primary_cat":"cs.LG","authors_text":"Joseph Manzano, Kevin Barker, Oceane Bel, Omer Subasi","submitted_at":"2023-12-05T20:40:05Z","abstract_excerpt":"With the advance of the powerful heterogeneous, parallel and distributed computing systems and ever increasing immense amount of data, machine learning has become an indispensable part of cutting-edge technology, scientific research and consumer products. In this study, we present a review of modern machine and deep learning. We provide a high-level overview for the latest advanced machine learning algorithms, applications, and frameworks. Our discussion encompasses parallel distributed learning, deep learning as well as federated learning. As a result, our work serves as an introductory text "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.03120","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2312.03120/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2312.03120","created_at":"2026-07-05T07:20:58.391341+00:00"},{"alias_kind":"arxiv_version","alias_value":"2312.03120v1","created_at":"2026-07-05T07:20:58.391341+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.03120","created_at":"2026-07-05T07:20:58.391341+00:00"},{"alias_kind":"pith_short_12","alias_value":"BT56YY2XIYGE","created_at":"2026-07-05T07:20:58.391341+00:00"},{"alias_kind":"pith_short_16","alias_value":"BT56YY2XIYGEGYK7","created_at":"2026-07-05T07:20:58.391341+00:00"},{"alias_kind":"pith_short_8","alias_value":"BT56YY2X","created_at":"2026-07-05T07:20:58.391341+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/BT56YY2XIYGEGYK7MZRJDFYP7J","json":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J.json","graph_json":"https://pith.science/api/pith-number/BT56YY2XIYGEGYK7MZRJDFYP7J/graph.json","events_json":"https://pith.science/api/pith-number/BT56YY2XIYGEGYK7MZRJDFYP7J/events.json","paper":"https://pith.science/paper/BT56YY2X"},"agent_actions":{"view_html":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J","download_json":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J.json","view_paper":"https://pith.science/paper/BT56YY2X","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2312.03120&json=true","fetch_graph":"https://pith.science/api/pith-number/BT56YY2XIYGEGYK7MZRJDFYP7J/graph.json","fetch_events":"https://pith.science/api/pith-number/BT56YY2XIYGEGYK7MZRJDFYP7J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J/action/storage_attestation","attest_author":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J/action/author_attestation","sign_citation":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J/action/citation_signature","submit_replication":"https://pith.science/pith/BT56YY2XIYGEGYK7MZRJDFYP7J/action/replication_record"}},"created_at":"2026-07-05T07:20:58.391341+00:00","updated_at":"2026-07-05T07:20:58.391341+00:00"}