{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:C6AOCYJH2EKUTZODQKK7JIDPTD","short_pith_number":"pith:C6AOCYJH","canonical_record":{"source":{"id":"1805.02483","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-07T12:50:36Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6a1b70f55e4e5226ada52c82e16ebad78faaa3068f85e9e5267439c46cbeb130","abstract_canon_sha256":"dd4f39c902309bd66ab4574925c84d85b9092a6696e61ecd96af9778a03b3944"},"schema_version":"1.0"},"canonical_sha256":"1780e16127d11549e5c38295f4a06f98dbc48a4e91c1090ab0456afa15ff3aa6","source":{"kind":"arxiv","id":"1805.02483","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.02483","created_at":"2026-05-18T00:08:14Z"},{"alias_kind":"arxiv_version","alias_value":"1805.02483v4","created_at":"2026-05-18T00:08:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.02483","created_at":"2026-05-18T00:08:14Z"},{"alias_kind":"pith_short_12","alias_value":"C6AOCYJH2EKU","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"C6AOCYJH2EKUTZOD","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"C6AOCYJH","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:C6AOCYJH2EKUTZODQKK7JIDPTD","target":"record","payload":{"canonical_record":{"source":{"id":"1805.02483","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-07T12:50:36Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"6a1b70f55e4e5226ada52c82e16ebad78faaa3068f85e9e5267439c46cbeb130","abstract_canon_sha256":"dd4f39c902309bd66ab4574925c84d85b9092a6696e61ecd96af9778a03b3944"},"schema_version":"1.0"},"canonical_sha256":"1780e16127d11549e5c38295f4a06f98dbc48a4e91c1090ab0456afa15ff3aa6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:08:14.864338Z","signature_b64":"TtuDc9pbZyvnt0cirKutyKYiuaRchUuZRDKiqc0VJxYaWuWRad7PZuUFYuV8C0684wbUfZ3YjEc+04rR6Qa8AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1780e16127d11549e5c38295f4a06f98dbc48a4e91c1090ab0456afa15ff3aa6","last_reissued_at":"2026-05-18T00:08:14.863983Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:08:14.863983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.02483","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:08:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RB43hJTZ+pYf1SgQnFgIBOmo5ipb7Q7JDy6XzyqwJFiLyXLECT84gFeQo0ccGBFiGjfN85i0vrxw0fqC3cSzAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T15:38:19.135816Z"},"content_sha256":"989f08dc177ae9cc78462528107c0135e7cc8b59858742968eeb85e06dcf81e8","schema_version":"1.0","event_id":"sha256:989f08dc177ae9cc78462528107c0135e7cc8b59858742968eeb85e06dcf81e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:C6AOCYJH2EKUTZODQKK7JIDPTD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Logistic Network Lasso","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Alexander Jung, Henrik Ambos, Nguyen Tran","submitted_at":"2018-05-07T12:50:36Z","abstract_excerpt":"We apply the network Lasso to solve binary classification and clustering problems for network-structured data. To this end, we generalize ordinary logistic regression to non-Euclidean data with an intrinsic network structure. The resulting \"logistic network Lasso\" amounts to solving a non-smooth convex regularized empirical risk minimization. The risk is measured using the logistic loss incurred over a small set of labeled nodes. For the regularization, we propose to use the total variation of the classifier requiring it to conform to the underlying network structure. A scalable implementation"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.02483","kind":"arxiv","version":4},"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":"2026-05-18T00:08:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"two6l2z6t8e7kLdiuY0EcjirZwtn2Z1OehiohwJSTZ+Dkpe9f1tjMgeF3si1RYKhkFpbonZxCSFJkhq7jw22Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T15:38:19.136156Z"},"content_sha256":"3442cf2a96145e7fdd4cffa5f03090ab976e80de7650e9c3cce08292ed3d84ff","schema_version":"1.0","event_id":"sha256:3442cf2a96145e7fdd4cffa5f03090ab976e80de7650e9c3cce08292ed3d84ff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C6AOCYJH2EKUTZODQKK7JIDPTD/bundle.json","state_url":"https://pith.science/pith/C6AOCYJH2EKUTZODQKK7JIDPTD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C6AOCYJH2EKUTZODQKK7JIDPTD/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":"2026-07-01T15:38:19Z","links":{"resolver":"https://pith.science/pith/C6AOCYJH2EKUTZODQKK7JIDPTD","bundle":"https://pith.science/pith/C6AOCYJH2EKUTZODQKK7JIDPTD/bundle.json","state":"https://pith.science/pith/C6AOCYJH2EKUTZODQKK7JIDPTD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C6AOCYJH2EKUTZODQKK7JIDPTD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:C6AOCYJH2EKUTZODQKK7JIDPTD","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":"dd4f39c902309bd66ab4574925c84d85b9092a6696e61ecd96af9778a03b3944","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-07T12:50:36Z","title_canon_sha256":"6a1b70f55e4e5226ada52c82e16ebad78faaa3068f85e9e5267439c46cbeb130"},"schema_version":"1.0","source":{"id":"1805.02483","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.02483","created_at":"2026-05-18T00:08:14Z"},{"alias_kind":"arxiv_version","alias_value":"1805.02483v4","created_at":"2026-05-18T00:08:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.02483","created_at":"2026-05-18T00:08:14Z"},{"alias_kind":"pith_short_12","alias_value":"C6AOCYJH2EKU","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"C6AOCYJH2EKUTZOD","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"C6AOCYJH","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:3442cf2a96145e7fdd4cffa5f03090ab976e80de7650e9c3cce08292ed3d84ff","target":"graph","created_at":"2026-05-18T00:08:14Z","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 apply the network Lasso to solve binary classification and clustering problems for network-structured data. To this end, we generalize ordinary logistic regression to non-Euclidean data with an intrinsic network structure. The resulting \"logistic network Lasso\" amounts to solving a non-smooth convex regularized empirical risk minimization. The risk is measured using the logistic loss incurred over a small set of labeled nodes. For the regularization, we propose to use the total variation of the classifier requiring it to conform to the underlying network structure. A scalable implementation","authors_text":"Alexander Jung, Henrik Ambos, Nguyen Tran","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-07T12:50:36Z","title":"The Logistic Network Lasso"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.02483","kind":"arxiv","version":4},"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":"sha256:989f08dc177ae9cc78462528107c0135e7cc8b59858742968eeb85e06dcf81e8","target":"record","created_at":"2026-05-18T00:08:14Z","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":"dd4f39c902309bd66ab4574925c84d85b9092a6696e61ecd96af9778a03b3944","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-07T12:50:36Z","title_canon_sha256":"6a1b70f55e4e5226ada52c82e16ebad78faaa3068f85e9e5267439c46cbeb130"},"schema_version":"1.0","source":{"id":"1805.02483","kind":"arxiv","version":4}},"canonical_sha256":"1780e16127d11549e5c38295f4a06f98dbc48a4e91c1090ab0456afa15ff3aa6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1780e16127d11549e5c38295f4a06f98dbc48a4e91c1090ab0456afa15ff3aa6","first_computed_at":"2026-05-18T00:08:14.863983Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:08:14.863983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TtuDc9pbZyvnt0cirKutyKYiuaRchUuZRDKiqc0VJxYaWuWRad7PZuUFYuV8C0684wbUfZ3YjEc+04rR6Qa8AQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:08:14.864338Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.02483","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:989f08dc177ae9cc78462528107c0135e7cc8b59858742968eeb85e06dcf81e8","sha256:3442cf2a96145e7fdd4cffa5f03090ab976e80de7650e9c3cce08292ed3d84ff"],"state_sha256":"220059995cf81be15a6bab5be8e01ee17e35fad5ddcbc21a00cec15788d02098"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zPPPJBk+udZPARX0TkkqsMsd+sgW2FwJQclipv8O39bk39qcu7TEJVG1xrcZjUHaMSgrBFdBbrVFkGZjLeouCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T15:38:19.138133Z","bundle_sha256":"a316a2347ced0663ed2756823f0a3432191dbb9344e3d4de5a203fe068023306"}}