{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:USTRB4CLVVKSKLCDZ7F6OBTSNQ","short_pith_number":"pith:USTRB4CL","canonical_record":{"source":{"id":"2408.10090","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-19T15:31:06Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"5b698a4b3ec972934c816a51f45e5feddc07e8a9c1752119bd15237791180f45","abstract_canon_sha256":"20a076a6ef1eb5805a1ccd3ded8c58ab0f10db3b2f9f21cc94cdfc9fe2d005e5"},"schema_version":"1.0"},"canonical_sha256":"a4a710f04bad55252c43cfcbe706726c3c767e7535223f381b7ea4b6155f6d92","source":{"kind":"arxiv","id":"2408.10090","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.10090","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"2408.10090v1","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.10090","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"USTRB4CLVVKS","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"pith_short_16","alias_value":"USTRB4CLVVKSKLCD","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"pith_short_8","alias_value":"USTRB4CL","created_at":"2026-07-05T08:56:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:USTRB4CLVVKSKLCDZ7F6OBTSNQ","target":"record","payload":{"canonical_record":{"source":{"id":"2408.10090","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-19T15:31:06Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"5b698a4b3ec972934c816a51f45e5feddc07e8a9c1752119bd15237791180f45","abstract_canon_sha256":"20a076a6ef1eb5805a1ccd3ded8c58ab0f10db3b2f9f21cc94cdfc9fe2d005e5"},"schema_version":"1.0"},"canonical_sha256":"a4a710f04bad55252c43cfcbe706726c3c767e7535223f381b7ea4b6155f6d92","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:56:51.246478Z","signature_b64":"k7W5oSkZQPCIF8zU+IPvLuf94dkvEbmNuumXsztLwQt2IJj7YGlF71Ppb6E0l5qoi1lh8xf0O/5rT9xsE+G9Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a4a710f04bad55252c43cfcbe706726c3c767e7535223f381b7ea4b6155f6d92","last_reissued_at":"2026-07-05T08:56:51.246064Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:56:51.246064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.10090","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Qkha9yu2w0WyB7gkIP0BwL+w4W5nsU8+F/8g1a6ZjTuR22DDYHNdT1s6xuB7fJZ0GsTm2SkhVNjXvOCvRmnMCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:45:00.722636Z"},"content_sha256":"dc34e13d060f75a9fc42e9b73cefd7d5dfa4b25c97f10e517794bf5ee2356298","schema_version":"1.0","event_id":"sha256:dc34e13d060f75a9fc42e9b73cefd7d5dfa4b25c97f10e517794bf5ee2356298"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:USTRB4CLVVKSKLCDZ7F6OBTSNQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Federated Frank-Wolfe Algorithm","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.LG","authors_text":"Ali Dadras, Alp Yurtsever, Karthik Prakhya, Sourasekhar Banerjee","submitted_at":"2024-08-19T15:31:06Z","abstract_excerpt":"Federated learning (FL) has gained a lot of attention in recent years for building privacy-preserving collaborative learning systems. However, FL algorithms for constrained machine learning problems are still limited, particularly when the projection step is costly. To this end, we propose a Federated Frank-Wolfe Algorithm (FedFW). FedFW features data privacy, low per-iteration cost, and communication of sparse signals. In the deterministic setting, FedFW achieves an $\\varepsilon$-suboptimal solution within $O(\\varepsilon^{-2})$ iterations for smooth and convex objectives, and $O(\\varepsilon^{"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.10090","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/2408.10090/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:56:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GVHYZBqsBf4DbGq+BbAsksMdyaxzdjLOe8hpkY5Zm58Iez+3gw6XpW7yA7Khhl7bvDKBHHpKDbegSWYKVzJkCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:45:00.723009Z"},"content_sha256":"d7d979e82376183dba88e4062ef80b1f68ac2e0af0a500fbb229e9225bed79df","schema_version":"1.0","event_id":"sha256:d7d979e82376183dba88e4062ef80b1f68ac2e0af0a500fbb229e9225bed79df"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ/bundle.json","state_url":"https://pith.science/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T17:45:00Z","links":{"resolver":"https://pith.science/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ","bundle":"https://pith.science/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ/bundle.json","state":"https://pith.science/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/USTRB4CLVVKSKLCDZ7F6OBTSNQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:USTRB4CLVVKSKLCDZ7F6OBTSNQ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"20a076a6ef1eb5805a1ccd3ded8c58ab0f10db3b2f9f21cc94cdfc9fe2d005e5","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-19T15:31:06Z","title_canon_sha256":"5b698a4b3ec972934c816a51f45e5feddc07e8a9c1752119bd15237791180f45"},"schema_version":"1.0","source":{"id":"2408.10090","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.10090","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"arxiv_version","alias_value":"2408.10090v1","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.10090","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"pith_short_12","alias_value":"USTRB4CLVVKS","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"pith_short_16","alias_value":"USTRB4CLVVKSKLCD","created_at":"2026-07-05T08:56:51Z"},{"alias_kind":"pith_short_8","alias_value":"USTRB4CL","created_at":"2026-07-05T08:56:51Z"}],"graph_snapshots":[{"event_id":"sha256:d7d979e82376183dba88e4062ef80b1f68ac2e0af0a500fbb229e9225bed79df","target":"graph","created_at":"2026-07-05T08:56:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2408.10090/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated learning (FL) has gained a lot of attention in recent years for building privacy-preserving collaborative learning systems. However, FL algorithms for constrained machine learning problems are still limited, particularly when the projection step is costly. To this end, we propose a Federated Frank-Wolfe Algorithm (FedFW). FedFW features data privacy, low per-iteration cost, and communication of sparse signals. In the deterministic setting, FedFW achieves an $\\varepsilon$-suboptimal solution within $O(\\varepsilon^{-2})$ iterations for smooth and convex objectives, and $O(\\varepsilon^{","authors_text":"Ali Dadras, Alp Yurtsever, Karthik Prakhya, Sourasekhar Banerjee","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-19T15:31:06Z","title":"Federated Frank-Wolfe Algorithm"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.10090","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:dc34e13d060f75a9fc42e9b73cefd7d5dfa4b25c97f10e517794bf5ee2356298","target":"record","created_at":"2026-07-05T08:56:51Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"20a076a6ef1eb5805a1ccd3ded8c58ab0f10db3b2f9f21cc94cdfc9fe2d005e5","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-08-19T15:31:06Z","title_canon_sha256":"5b698a4b3ec972934c816a51f45e5feddc07e8a9c1752119bd15237791180f45"},"schema_version":"1.0","source":{"id":"2408.10090","kind":"arxiv","version":1}},"canonical_sha256":"a4a710f04bad55252c43cfcbe706726c3c767e7535223f381b7ea4b6155f6d92","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a4a710f04bad55252c43cfcbe706726c3c767e7535223f381b7ea4b6155f6d92","first_computed_at":"2026-07-05T08:56:51.246064Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:56:51.246064Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"k7W5oSkZQPCIF8zU+IPvLuf94dkvEbmNuumXsztLwQt2IJj7YGlF71Ppb6E0l5qoi1lh8xf0O/5rT9xsE+G9Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:56:51.246478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.10090","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dc34e13d060f75a9fc42e9b73cefd7d5dfa4b25c97f10e517794bf5ee2356298","sha256:d7d979e82376183dba88e4062ef80b1f68ac2e0af0a500fbb229e9225bed79df"],"state_sha256":"208be1184ace206dbeb61f59efccdcbb6b0a52cc337eb38af4b7f28808379d01"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"loIWd+JN4Ol0vbxXShv4/dk8XhlTBu/yXnMt8MFM9igFUj7Ee/ENUUoLV2o7VlSUhrkDMJrDcnw9pA36mV4OCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:45:00.724940Z","bundle_sha256":"fd2797110a21f995d6201a0a35a4b2a6feca71201b748e5809e8dbbfd4c99256"}}