{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:PTIENVVBXY2GJKIFDEDIRUYPEC","short_pith_number":"pith:PTIENVVB","canonical_record":{"source":{"id":"2010.13413","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2020-10-26T08:23:13Z","cross_cats_sorted":[],"title_canon_sha256":"f491381f870fa7c7760c0a0bd6da120f1f71e53760478669f2ba7c7f51c69775","abstract_canon_sha256":"baaeceef55b38c76833d41d644fb67b81668dbece65f31d97b62c175a0bfe89a"},"schema_version":"1.0"},"canonical_sha256":"7cd046d6a1be3464a905190688d30f2087fed90329e248500f883a7c70cde027","source":{"kind":"arxiv","id":"2010.13413","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.13413","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"arxiv_version","alias_value":"2010.13413v2","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.13413","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"pith_short_12","alias_value":"PTIENVVBXY2G","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"pith_short_16","alias_value":"PTIENVVBXY2GJKIF","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"pith_short_8","alias_value":"PTIENVVB","created_at":"2026-07-05T02:13:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:PTIENVVBXY2GJKIFDEDIRUYPEC","target":"record","payload":{"canonical_record":{"source":{"id":"2010.13413","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2020-10-26T08:23:13Z","cross_cats_sorted":[],"title_canon_sha256":"f491381f870fa7c7760c0a0bd6da120f1f71e53760478669f2ba7c7f51c69775","abstract_canon_sha256":"baaeceef55b38c76833d41d644fb67b81668dbece65f31d97b62c175a0bfe89a"},"schema_version":"1.0"},"canonical_sha256":"7cd046d6a1be3464a905190688d30f2087fed90329e248500f883a7c70cde027","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:13:03.881623Z","signature_b64":"W6Bfhs7doYuAqCpjgUV+KpQax0T7et+qbWZzwRYh0mJjUT8LXCe3O0j0PFsG5PJupzxrTCwN55o3+oEsUoKOBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7cd046d6a1be3464a905190688d30f2087fed90329e248500f883a7c70cde027","last_reissued_at":"2026-07-05T02:13:03.881228Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:13:03.881228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.13413","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:13:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0k9VUDy/kdXqk9/nb4+7f8ODTuYfqZe+IuMrKbwxJxwZO2LCMXmvFeV0GQzi/izw/rMYRp1/eDOjHiSvM7yPBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T21:53:29.552790Z"},"content_sha256":"924e5fcd41c8fc9143eb1864260fca359c9defaead3352794592eb6b14baa0a0","schema_version":"1.0","event_id":"sha256:924e5fcd41c8fc9143eb1864260fca359c9defaead3352794592eb6b14baa0a0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:PTIENVVBXY2GJKIFDEDIRUYPEC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Node-Adaptive Regularization for Graph Signal Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Elvin Isufi, Geert Leus, Maosheng Yang, Mario Coutino","submitted_at":"2020-10-26T08:23:13Z","abstract_excerpt":"A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem. In this paper, we propose a node-adaptive regularization for graph signal reconstruction, which surmounts the conventional Tikhonov regularization, giving rise to more degrees of freedom; hence, an improved performance. We formulate the node-adaptive graph signal denoising problem, study its bias-variance trade-off, and identify conditions under which a lower mean squared error and variance can be obtained with respect to Tikhonov r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.13413","kind":"arxiv","version":2},"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/2010.13413/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":"2026-07-05T02:13:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dZgJlLbB+GwTdw2RKL3wEBwgNu7mKvf7oIVhlGTbcNuBqtDrAP5z9AaEoLYLjrcpw5ee0wPv3nNeKRMMj0tTBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T21:53:29.553338Z"},"content_sha256":"ecc7d6b96539e45927187d1544dda4e64a9e10be885b1cf71589bcfd4f676ac5","schema_version":"1.0","event_id":"sha256:ecc7d6b96539e45927187d1544dda4e64a9e10be885b1cf71589bcfd4f676ac5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PTIENVVBXY2GJKIFDEDIRUYPEC/bundle.json","state_url":"https://pith.science/pith/PTIENVVBXY2GJKIFDEDIRUYPEC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PTIENVVBXY2GJKIFDEDIRUYPEC/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":"2026-08-23T21:53:29Z","links":{"resolver":"https://pith.science/pith/PTIENVVBXY2GJKIFDEDIRUYPEC","bundle":"https://pith.science/pith/PTIENVVBXY2GJKIFDEDIRUYPEC/bundle.json","state":"https://pith.science/pith/PTIENVVBXY2GJKIFDEDIRUYPEC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PTIENVVBXY2GJKIFDEDIRUYPEC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:PTIENVVBXY2GJKIFDEDIRUYPEC","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":"baaeceef55b38c76833d41d644fb67b81668dbece65f31d97b62c175a0bfe89a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2020-10-26T08:23:13Z","title_canon_sha256":"f491381f870fa7c7760c0a0bd6da120f1f71e53760478669f2ba7c7f51c69775"},"schema_version":"1.0","source":{"id":"2010.13413","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.13413","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"arxiv_version","alias_value":"2010.13413v2","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.13413","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"pith_short_12","alias_value":"PTIENVVBXY2G","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"pith_short_16","alias_value":"PTIENVVBXY2GJKIF","created_at":"2026-07-05T02:13:03Z"},{"alias_kind":"pith_short_8","alias_value":"PTIENVVB","created_at":"2026-07-05T02:13:03Z"}],"graph_snapshots":[{"event_id":"sha256:ecc7d6b96539e45927187d1544dda4e64a9e10be885b1cf71589bcfd4f676ac5","target":"graph","created_at":"2026-07-05T02:13:03Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2010.13413/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A critical task in graph signal processing is to estimate the true signal from noisy observations over a subset of nodes, also known as the reconstruction problem. In this paper, we propose a node-adaptive regularization for graph signal reconstruction, which surmounts the conventional Tikhonov regularization, giving rise to more degrees of freedom; hence, an improved performance. We formulate the node-adaptive graph signal denoising problem, study its bias-variance trade-off, and identify conditions under which a lower mean squared error and variance can be obtained with respect to Tikhonov r","authors_text":"Elvin Isufi, Geert Leus, Maosheng Yang, Mario Coutino","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2020-10-26T08:23:13Z","title":"Node-Adaptive Regularization for Graph Signal Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.13413","kind":"arxiv","version":2},"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":"sha256:924e5fcd41c8fc9143eb1864260fca359c9defaead3352794592eb6b14baa0a0","target":"record","created_at":"2026-07-05T02:13:03Z","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":"baaeceef55b38c76833d41d644fb67b81668dbece65f31d97b62c175a0bfe89a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2020-10-26T08:23:13Z","title_canon_sha256":"f491381f870fa7c7760c0a0bd6da120f1f71e53760478669f2ba7c7f51c69775"},"schema_version":"1.0","source":{"id":"2010.13413","kind":"arxiv","version":2}},"canonical_sha256":"7cd046d6a1be3464a905190688d30f2087fed90329e248500f883a7c70cde027","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7cd046d6a1be3464a905190688d30f2087fed90329e248500f883a7c70cde027","first_computed_at":"2026-07-05T02:13:03.881228Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:13:03.881228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W6Bfhs7doYuAqCpjgUV+KpQax0T7et+qbWZzwRYh0mJjUT8LXCe3O0j0PFsG5PJupzxrTCwN55o3+oEsUoKOBg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:13:03.881623Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.13413","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:924e5fcd41c8fc9143eb1864260fca359c9defaead3352794592eb6b14baa0a0","sha256:ecc7d6b96539e45927187d1544dda4e64a9e10be885b1cf71589bcfd4f676ac5"],"state_sha256":"cae55ab7fd7c6087b95ebd7ddf7dcdac32f21d26c1c7509f1ce02de7de2130e4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JwPzkopjWfwTLADdR+0W1mCAjyb1GEkY87bOUuzsDToJUp6GKgH90wv4Ahy5dIxxFgc+lPdnf8Q6+S+954d2DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T21:53:29.557556Z","bundle_sha256":"46891b3c54f6ead006192b19dec4d2efe14621e2571cb1620fcd16db01ab70bd"}}