{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:GZ6RELO4OODAXIPP4WROJ37RFJ","short_pith_number":"pith:GZ6RELO4","canonical_record":{"source":{"id":"1806.01003","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-06-04T08:19:27Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"4e0e795e714d3908bbf97ac7976513b5afcd47cc0cc68953a7c53329d0b5f8b5","abstract_canon_sha256":"f28e3715e40232c991130a8ea3a363f9bae11a8d0f1eeba4082092851d8f7efa"},"schema_version":"1.0"},"canonical_sha256":"367d122ddc73860ba1efe5a2e4eff12a71da3a79495f97298869c5e21b350c3e","source":{"kind":"arxiv","id":"1806.01003","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.01003","created_at":"2026-05-18T00:14:17Z"},{"alias_kind":"arxiv_version","alias_value":"1806.01003v1","created_at":"2026-05-18T00:14:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.01003","created_at":"2026-05-18T00:14:17Z"},{"alias_kind":"pith_short_12","alias_value":"GZ6RELO4OODA","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GZ6RELO4OODAXIPP","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GZ6RELO4","created_at":"2026-05-18T12:32:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:GZ6RELO4OODAXIPP4WROJ37RFJ","target":"record","payload":{"canonical_record":{"source":{"id":"1806.01003","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-06-04T08:19:27Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"4e0e795e714d3908bbf97ac7976513b5afcd47cc0cc68953a7c53329d0b5f8b5","abstract_canon_sha256":"f28e3715e40232c991130a8ea3a363f9bae11a8d0f1eeba4082092851d8f7efa"},"schema_version":"1.0"},"canonical_sha256":"367d122ddc73860ba1efe5a2e4eff12a71da3a79495f97298869c5e21b350c3e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:17.750054Z","signature_b64":"BZQuxYMpa7Hm7/Rk7PtVDgeO+hOeuYkc5CwgRnJgn6GBQ4Mpf5tnKEuzldxz0NhowBMxacXcOwn69C3yg7JeBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"367d122ddc73860ba1efe5a2e4eff12a71da3a79495f97298869c5e21b350c3e","last_reissued_at":"2026-05-18T00:14:17.749544Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:17.749544Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.01003","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":"2026-05-18T00:14:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VwEDf6cqwzOyznhkotFYMJsngsUkYO+zB//ntZRIfgyvBjgx9E6DJ38Gz8TS4DRrmTUd+8Zl1jzTIncYSSyjAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T22:59:34.154774Z"},"content_sha256":"9ff2b7dcfbca3d9f2cda0523f48f2dc5562f6922ba6de2765cb2eac8e1c53705","schema_version":"1.0","event_id":"sha256:9ff2b7dcfbca3d9f2cda0523f48f2dc5562f6922ba6de2765cb2eac8e1c53705"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:GZ6RELO4OODAXIPP4WROJ37RFJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Distributed Learning from Interactions in Social Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.SY","authors_text":"Angelo Coluccia, Francesco Sasso, Giuseppe Notarstefano","submitted_at":"2018-06-04T08:19:27Z","abstract_excerpt":"We consider a network scenario in which agents can evaluate each other according to a score graph that models some interactions. The goal is to design a distributed protocol, run by the agents, that allows them to learn their unknown state among a finite set of possible values. We propose a Bayesian framework in which scores and states are associated to probabilistic events with unknown parameters and hyperparameters, respectively. We show that each agent can learn its state by means of a local Bayesian classifier and a (centralized) Maximum-Likelihood (ML) estimator of parameter-hyperparamete"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.01003","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:14:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2aB19bufm5MFqLyKDNA9ftqdDGQXMJoyY/5Q7uT7tw1XLVjRoTJq6rBjCIcJAYQdga58akXQMt97gLZJfcFrCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T22:59:34.155119Z"},"content_sha256":"472fb69a644deb3c5ec01721446077c7b93b5be680a55e177f51aa47fad34111","schema_version":"1.0","event_id":"sha256:472fb69a644deb3c5ec01721446077c7b93b5be680a55e177f51aa47fad34111"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GZ6RELO4OODAXIPP4WROJ37RFJ/bundle.json","state_url":"https://pith.science/pith/GZ6RELO4OODAXIPP4WROJ37RFJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GZ6RELO4OODAXIPP4WROJ37RFJ/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":"2026-06-01T22:59:34Z","links":{"resolver":"https://pith.science/pith/GZ6RELO4OODAXIPP4WROJ37RFJ","bundle":"https://pith.science/pith/GZ6RELO4OODAXIPP4WROJ37RFJ/bundle.json","state":"https://pith.science/pith/GZ6RELO4OODAXIPP4WROJ37RFJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GZ6RELO4OODAXIPP4WROJ37RFJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GZ6RELO4OODAXIPP4WROJ37RFJ","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":"f28e3715e40232c991130a8ea3a363f9bae11a8d0f1eeba4082092851d8f7efa","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-06-04T08:19:27Z","title_canon_sha256":"4e0e795e714d3908bbf97ac7976513b5afcd47cc0cc68953a7c53329d0b5f8b5"},"schema_version":"1.0","source":{"id":"1806.01003","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.01003","created_at":"2026-05-18T00:14:17Z"},{"alias_kind":"arxiv_version","alias_value":"1806.01003v1","created_at":"2026-05-18T00:14:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.01003","created_at":"2026-05-18T00:14:17Z"},{"alias_kind":"pith_short_12","alias_value":"GZ6RELO4OODA","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GZ6RELO4OODAXIPP","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GZ6RELO4","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:472fb69a644deb3c5ec01721446077c7b93b5be680a55e177f51aa47fad34111","target":"graph","created_at":"2026-05-18T00:14:17Z","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"},"paper":{"abstract_excerpt":"We consider a network scenario in which agents can evaluate each other according to a score graph that models some interactions. The goal is to design a distributed protocol, run by the agents, that allows them to learn their unknown state among a finite set of possible values. We propose a Bayesian framework in which scores and states are associated to probabilistic events with unknown parameters and hyperparameters, respectively. We show that each agent can learn its state by means of a local Bayesian classifier and a (centralized) Maximum-Likelihood (ML) estimator of parameter-hyperparamete","authors_text":"Angelo Coluccia, Francesco Sasso, Giuseppe Notarstefano","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-06-04T08:19:27Z","title":"Distributed Learning from Interactions in Social Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.01003","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":"sha256:9ff2b7dcfbca3d9f2cda0523f48f2dc5562f6922ba6de2765cb2eac8e1c53705","target":"record","created_at":"2026-05-18T00:14:17Z","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":"f28e3715e40232c991130a8ea3a363f9bae11a8d0f1eeba4082092851d8f7efa","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SY","submitted_at":"2018-06-04T08:19:27Z","title_canon_sha256":"4e0e795e714d3908bbf97ac7976513b5afcd47cc0cc68953a7c53329d0b5f8b5"},"schema_version":"1.0","source":{"id":"1806.01003","kind":"arxiv","version":1}},"canonical_sha256":"367d122ddc73860ba1efe5a2e4eff12a71da3a79495f97298869c5e21b350c3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"367d122ddc73860ba1efe5a2e4eff12a71da3a79495f97298869c5e21b350c3e","first_computed_at":"2026-05-18T00:14:17.749544Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:17.749544Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BZQuxYMpa7Hm7/Rk7PtVDgeO+hOeuYkc5CwgRnJgn6GBQ4Mpf5tnKEuzldxz0NhowBMxacXcOwn69C3yg7JeBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:17.750054Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.01003","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9ff2b7dcfbca3d9f2cda0523f48f2dc5562f6922ba6de2765cb2eac8e1c53705","sha256:472fb69a644deb3c5ec01721446077c7b93b5be680a55e177f51aa47fad34111"],"state_sha256":"556a89f0e7fee0282cf2e0978b2d135a33ac5e50cc860707935d4925cedbc44d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dI/K7101OFwYuO0C4zR9aKF/x/1/bTaDY7Fy6Ae55Jpensy7DZRW3D4mh9P1s03InVu2r6nAniPHZhaMPQx9Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T22:59:34.157180Z","bundle_sha256":"7a16f4058644b4b56629434e299f88b880544a78ffff5f4feb460603483ea21d"}}