{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:DQOXDS7KW7IYLNNBK22MGAR75U","short_pith_number":"pith:DQOXDS7K","canonical_record":{"source":{"id":"1802.06307","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-17T23:21:20Z","cross_cats_sorted":[],"title_canon_sha256":"ba11086cec4c54c3a7f08a9f9511f5abd40c46e79db7d7a90843af2c2273717a","abstract_canon_sha256":"2ed70205036d5097dd9c3169a50eed8761e22eafed5b5daca278899a197fb4ab"},"schema_version":"1.0"},"canonical_sha256":"1c1d71cbeab7d185b5a156b4c3023fed0919448d7f94dfd16ec2f6164ee995a8","source":{"kind":"arxiv","id":"1802.06307","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.06307","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"arxiv_version","alias_value":"1802.06307v1","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.06307","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"pith_short_12","alias_value":"DQOXDS7KW7IY","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_16","alias_value":"DQOXDS7KW7IYLNNB","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_8","alias_value":"DQOXDS7K","created_at":"2026-05-18T12:32:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:DQOXDS7KW7IYLNNBK22MGAR75U","target":"record","payload":{"canonical_record":{"source":{"id":"1802.06307","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-17T23:21:20Z","cross_cats_sorted":[],"title_canon_sha256":"ba11086cec4c54c3a7f08a9f9511f5abd40c46e79db7d7a90843af2c2273717a","abstract_canon_sha256":"2ed70205036d5097dd9c3169a50eed8761e22eafed5b5daca278899a197fb4ab"},"schema_version":"1.0"},"canonical_sha256":"1c1d71cbeab7d185b5a156b4c3023fed0919448d7f94dfd16ec2f6164ee995a8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:23:03.732212Z","signature_b64":"v0E8RTUiHd7s09ClsL1zykXb1ASz1xH0HXsqvPAr9LxGp2C8ddtxaO4n0SnCFmcbYDa2jOhmz0CKNFuTx9+fAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c1d71cbeab7d185b5a156b4c3023fed0919448d7f94dfd16ec2f6164ee995a8","last_reissued_at":"2026-05-18T00:23:03.731724Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:23:03.731724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.06307","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":"2026-05-18T00:23:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NqwvIrXoH8XwHqh8S0hsetLAV8b/wryD5mXszPUZ6y1Ijv5IRjx0RFHEb4y8SLuPShYMGtOVWVBRsxNjP+jeCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T01:26:09.707665Z"},"content_sha256":"b0b743b02c436b888c558eaa8233622aa673a6aeeb2243dacfb28f822f13f7b6","schema_version":"1.0","event_id":"sha256:b0b743b02c436b888c558eaa8233622aa673a6aeeb2243dacfb28f822f13f7b6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:DQOXDS7KW7IYLNNBK22MGAR75U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Out-of-sample extension of graph adjacency spectral embedding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ML","authors_text":"Carey E. Priebe, Farbod Roosta-Khorasani, Keith Levin, Michael W. Mahoney","submitted_at":"2018-02-17T23:21:20Z","abstract_excerpt":"Many popular dimensionality reduction procedures have out-of-sample extensions, which allow a practitioner to apply a learned embedding to observations not seen in the initial training sample. In this work, we consider the problem of obtaining an out-of-sample extension for the adjacency spectral embedding, a procedure for embedding the vertices of a graph into Euclidean space. We present two different approaches to this problem, one based on a least-squares objective and the other based on a maximum-likelihood formulation. We show that if the graph of interest is drawn according to a certain "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.06307","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":"2026-05-18T00:23:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0vsy4O8DoAkMPlR3M1Gbj1qAgkByz7QlI33uZOKM2mI2VP+gH85kZSGFsVlfYMoqyxhU1oZiUxFGteLCCLXfCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T01:26:09.708415Z"},"content_sha256":"9017bcb0b610c0c7de3e7e5e2551a3cadbcad77dfc3c5d75c5b575fd8d27734c","schema_version":"1.0","event_id":"sha256:9017bcb0b610c0c7de3e7e5e2551a3cadbcad77dfc3c5d75c5b575fd8d27734c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DQOXDS7KW7IYLNNBK22MGAR75U/bundle.json","state_url":"https://pith.science/pith/DQOXDS7KW7IYLNNBK22MGAR75U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DQOXDS7KW7IYLNNBK22MGAR75U/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":"2026-06-12T01:26:09Z","links":{"resolver":"https://pith.science/pith/DQOXDS7KW7IYLNNBK22MGAR75U","bundle":"https://pith.science/pith/DQOXDS7KW7IYLNNBK22MGAR75U/bundle.json","state":"https://pith.science/pith/DQOXDS7KW7IYLNNBK22MGAR75U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DQOXDS7KW7IYLNNBK22MGAR75U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:DQOXDS7KW7IYLNNBK22MGAR75U","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":"2ed70205036d5097dd9c3169a50eed8761e22eafed5b5daca278899a197fb4ab","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-17T23:21:20Z","title_canon_sha256":"ba11086cec4c54c3a7f08a9f9511f5abd40c46e79db7d7a90843af2c2273717a"},"schema_version":"1.0","source":{"id":"1802.06307","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.06307","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"arxiv_version","alias_value":"1802.06307v1","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.06307","created_at":"2026-05-18T00:23:03Z"},{"alias_kind":"pith_short_12","alias_value":"DQOXDS7KW7IY","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_16","alias_value":"DQOXDS7KW7IYLNNB","created_at":"2026-05-18T12:32:19Z"},{"alias_kind":"pith_short_8","alias_value":"DQOXDS7K","created_at":"2026-05-18T12:32:19Z"}],"graph_snapshots":[{"event_id":"sha256:9017bcb0b610c0c7de3e7e5e2551a3cadbcad77dfc3c5d75c5b575fd8d27734c","target":"graph","created_at":"2026-05-18T00:23:03Z","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":"Many popular dimensionality reduction procedures have out-of-sample extensions, which allow a practitioner to apply a learned embedding to observations not seen in the initial training sample. In this work, we consider the problem of obtaining an out-of-sample extension for the adjacency spectral embedding, a procedure for embedding the vertices of a graph into Euclidean space. We present two different approaches to this problem, one based on a least-squares objective and the other based on a maximum-likelihood formulation. We show that if the graph of interest is drawn according to a certain ","authors_text":"Carey E. Priebe, Farbod Roosta-Khorasani, Keith Levin, Michael W. Mahoney","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-17T23:21:20Z","title":"Out-of-sample extension of graph adjacency spectral embedding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.06307","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:b0b743b02c436b888c558eaa8233622aa673a6aeeb2243dacfb28f822f13f7b6","target":"record","created_at":"2026-05-18T00:23:03Z","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":"2ed70205036d5097dd9c3169a50eed8761e22eafed5b5daca278899a197fb4ab","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-02-17T23:21:20Z","title_canon_sha256":"ba11086cec4c54c3a7f08a9f9511f5abd40c46e79db7d7a90843af2c2273717a"},"schema_version":"1.0","source":{"id":"1802.06307","kind":"arxiv","version":1}},"canonical_sha256":"1c1d71cbeab7d185b5a156b4c3023fed0919448d7f94dfd16ec2f6164ee995a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c1d71cbeab7d185b5a156b4c3023fed0919448d7f94dfd16ec2f6164ee995a8","first_computed_at":"2026-05-18T00:23:03.731724Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:03.731724Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v0E8RTUiHd7s09ClsL1zykXb1ASz1xH0HXsqvPAr9LxGp2C8ddtxaO4n0SnCFmcbYDa2jOhmz0CKNFuTx9+fAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:03.732212Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.06307","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b0b743b02c436b888c558eaa8233622aa673a6aeeb2243dacfb28f822f13f7b6","sha256:9017bcb0b610c0c7de3e7e5e2551a3cadbcad77dfc3c5d75c5b575fd8d27734c"],"state_sha256":"8c751486ce7f26dbdfb33a29f6eb902700fa0af1cc9c1e3995a1f164ed1857c0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A4oyYyYMVQx1+U7bGwk6pAFNLlhNCHdE50tkwS0jdWK1fBVKfLrlvredlpeUYX89kY9bzV3/z8bevQaXfumtAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-12T01:26:09.712721Z","bundle_sha256":"d694be4c3f07610cee17488dd0b0e754fc313c1b5231ea928c75294787f8ebc2"}}