{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:H2HDZ6JW7MJAANGVCKYR7TKCJG","short_pith_number":"pith:H2HDZ6JW","canonical_record":{"source":{"id":"1408.5286","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-08-22T13:03:00Z","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"title_canon_sha256":"a8c75cd377cc524759304211f06d3103573dd1f16df0b0ac64ca04fa5c13758d","abstract_canon_sha256":"cb152d560c455614d23d65e893916b764826b560bc582762010788a6288490b8"},"schema_version":"1.0"},"canonical_sha256":"3e8e3cf936fb120034d512b11fcd4249bea8b5e0507625f490e2459e375c7f43","source":{"kind":"arxiv","id":"1408.5286","version":7},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1408.5286","created_at":"2026-05-18T00:44:46Z"},{"alias_kind":"arxiv_version","alias_value":"1408.5286v7","created_at":"2026-05-18T00:44:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1408.5286","created_at":"2026-05-18T00:44:46Z"},{"alias_kind":"pith_short_12","alias_value":"H2HDZ6JW7MJA","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_16","alias_value":"H2HDZ6JW7MJAANGV","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_8","alias_value":"H2HDZ6JW","created_at":"2026-05-18T12:28:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:H2HDZ6JW7MJAANGVCKYR7TKCJG","target":"record","payload":{"canonical_record":{"source":{"id":"1408.5286","kind":"arxiv","version":7},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-08-22T13:03:00Z","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"title_canon_sha256":"a8c75cd377cc524759304211f06d3103573dd1f16df0b0ac64ca04fa5c13758d","abstract_canon_sha256":"cb152d560c455614d23d65e893916b764826b560bc582762010788a6288490b8"},"schema_version":"1.0"},"canonical_sha256":"3e8e3cf936fb120034d512b11fcd4249bea8b5e0507625f490e2459e375c7f43","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:44:46.287398Z","signature_b64":"9v6QJmWmf9c1dLNscGJmHDO4XAiQvebsKhJFOtgYpvAZ1+pODv/Pnn9k3gYaNE10sC97VFYJHRH5l3iUhbQfCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e8e3cf936fb120034d512b11fcd4249bea8b5e0507625f490e2459e375c7f43","last_reissued_at":"2026-05-18T00:44:46.286918Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:44:46.286918Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1408.5286","source_version":7,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:44:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j8fvMGpzt4s9K6lzSYMe1EVr9oZCt0Xwy9z21IgwK51zmDJJFwG234mYUQFPyJBKqJEJxlXLN5Y7ZdP3HInxBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T19:18:50.268241Z"},"content_sha256":"a4a81b9a6f9290f710bbc0c6d1368e7185b308037a7ad46bffc1b1c675fc0354","schema_version":"1.0","event_id":"sha256:a4a81b9a6f9290f710bbc0c6d1368e7185b308037a7ad46bffc1b1c675fc0354"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:H2HDZ6JW7MJAANGVCKYR7TKCJG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Designing labeled graph classifiers by exploiting the R\\'enyi entropy of the dissimilarity representation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","math.IT","stat.ML"],"primary_cat":"cs.CV","authors_text":"Lorenzo Livi","submitted_at":"2014-08-22T13:03:00Z","abstract_excerpt":"Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures, are nowadays available and tested for various datasets of labeled graphs. However, the design of effective learning procedures operating in the space of labeled graphs is still a challenging problem, especially from the computational complexity viewpoint. In this paper, we present a major improvement of a general-purpose classifier for graphs, which is concei"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1408.5286","kind":"arxiv","version":7},"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":"2026-05-18T00:44:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5lae8nzaOXVhK8kE0FqaCjzv74/QvuhT04cxMmITOqTo4saY9Hw78JEJMDoYIPx1ugKRPJD0ECl5eX65nVTzDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-05T19:18:50.268619Z"},"content_sha256":"0a43fc631d45ec486b1d88ede4fb87ba5c794c92728026aa265bd885df18798d","schema_version":"1.0","event_id":"sha256:0a43fc631d45ec486b1d88ede4fb87ba5c794c92728026aa265bd885df18798d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG/bundle.json","state_url":"https://pith.science/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG/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":"2026-06-05T19:18:50Z","links":{"resolver":"https://pith.science/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG","bundle":"https://pith.science/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG/bundle.json","state":"https://pith.science/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H2HDZ6JW7MJAANGVCKYR7TKCJG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:H2HDZ6JW7MJAANGVCKYR7TKCJG","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":"cb152d560c455614d23d65e893916b764826b560bc582762010788a6288490b8","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-08-22T13:03:00Z","title_canon_sha256":"a8c75cd377cc524759304211f06d3103573dd1f16df0b0ac64ca04fa5c13758d"},"schema_version":"1.0","source":{"id":"1408.5286","kind":"arxiv","version":7}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1408.5286","created_at":"2026-05-18T00:44:46Z"},{"alias_kind":"arxiv_version","alias_value":"1408.5286v7","created_at":"2026-05-18T00:44:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1408.5286","created_at":"2026-05-18T00:44:46Z"},{"alias_kind":"pith_short_12","alias_value":"H2HDZ6JW7MJA","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_16","alias_value":"H2HDZ6JW7MJAANGV","created_at":"2026-05-18T12:28:30Z"},{"alias_kind":"pith_short_8","alias_value":"H2HDZ6JW","created_at":"2026-05-18T12:28:30Z"}],"graph_snapshots":[{"event_id":"sha256:0a43fc631d45ec486b1d88ede4fb87ba5c794c92728026aa265bd885df18798d","target":"graph","created_at":"2026-05-18T00:44:46Z","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":"Representing patterns as labeled graphs is becoming increasingly common in the broad field of computational intelligence. Accordingly, a wide repertoire of pattern recognition tools, such as classifiers and knowledge discovery procedures, are nowadays available and tested for various datasets of labeled graphs. However, the design of effective learning procedures operating in the space of labeled graphs is still a challenging problem, especially from the computational complexity viewpoint. In this paper, we present a major improvement of a general-purpose classifier for graphs, which is concei","authors_text":"Lorenzo Livi","cross_cats":["cs.IT","math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-08-22T13:03:00Z","title":"Designing labeled graph classifiers by exploiting the R\\'enyi entropy of the dissimilarity representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1408.5286","kind":"arxiv","version":7},"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:a4a81b9a6f9290f710bbc0c6d1368e7185b308037a7ad46bffc1b1c675fc0354","target":"record","created_at":"2026-05-18T00:44:46Z","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":"cb152d560c455614d23d65e893916b764826b560bc582762010788a6288490b8","cross_cats_sorted":["cs.IT","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-08-22T13:03:00Z","title_canon_sha256":"a8c75cd377cc524759304211f06d3103573dd1f16df0b0ac64ca04fa5c13758d"},"schema_version":"1.0","source":{"id":"1408.5286","kind":"arxiv","version":7}},"canonical_sha256":"3e8e3cf936fb120034d512b11fcd4249bea8b5e0507625f490e2459e375c7f43","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e8e3cf936fb120034d512b11fcd4249bea8b5e0507625f490e2459e375c7f43","first_computed_at":"2026-05-18T00:44:46.286918Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:44:46.286918Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9v6QJmWmf9c1dLNscGJmHDO4XAiQvebsKhJFOtgYpvAZ1+pODv/Pnn9k3gYaNE10sC97VFYJHRH5l3iUhbQfCQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:44:46.287398Z","signed_message":"canonical_sha256_bytes"},"source_id":"1408.5286","source_kind":"arxiv","source_version":7}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a4a81b9a6f9290f710bbc0c6d1368e7185b308037a7ad46bffc1b1c675fc0354","sha256:0a43fc631d45ec486b1d88ede4fb87ba5c794c92728026aa265bd885df18798d"],"state_sha256":"88c2d39b235c469da54404a18c6e79458fbcbf7109a8b225044344c6b20d1536"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nzpJ8hxHyhy8+NNXRDz/1Y1QG/PgiltCaYooxkAaORh9OGiAGHlkGZbnDCW7icgP11hH2TpTJFx5MPNlOvWCCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-05T19:18:50.271049Z","bundle_sha256":"55a4eb476c9972fec29458d40b87d92cf37d44d630f099c03bb8881d3ab6c855"}}