{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:6OYR7G3EKML5ZS6NG77L7VC4MX","short_pith_number":"pith:6OYR7G3E","canonical_record":{"source":{"id":"1606.05918","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-06-19T22:17:05Z","cross_cats_sorted":["cs.DM"],"title_canon_sha256":"1b7ab948ab706f94e099c291cc06e7e0c5ce3272fa059f0b13975a0cecfb96a1","abstract_canon_sha256":"27758d43ded4eb7fc16849f4dbb37e7e45c95763e9fa5da68bca914fce381e0b"},"schema_version":"1.0"},"canonical_sha256":"f3b11f9b645317dccbcd37febfd45c65e7ff49dea3cf49968e643a45dcd2f6b2","source":{"kind":"arxiv","id":"1606.05918","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.05918","created_at":"2026-05-18T00:38:18Z"},{"alias_kind":"arxiv_version","alias_value":"1606.05918v2","created_at":"2026-05-18T00:38:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.05918","created_at":"2026-05-18T00:38:18Z"},{"alias_kind":"pith_short_12","alias_value":"6OYR7G3EKML5","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"6OYR7G3EKML5ZS6N","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"6OYR7G3E","created_at":"2026-05-18T12:30:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:6OYR7G3EKML5ZS6NG77L7VC4MX","target":"record","payload":{"canonical_record":{"source":{"id":"1606.05918","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-06-19T22:17:05Z","cross_cats_sorted":["cs.DM"],"title_canon_sha256":"1b7ab948ab706f94e099c291cc06e7e0c5ce3272fa059f0b13975a0cecfb96a1","abstract_canon_sha256":"27758d43ded4eb7fc16849f4dbb37e7e45c95763e9fa5da68bca914fce381e0b"},"schema_version":"1.0"},"canonical_sha256":"f3b11f9b645317dccbcd37febfd45c65e7ff49dea3cf49968e643a45dcd2f6b2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:38:18.700624Z","signature_b64":"+cIZDHvvWenQAI16UQKntpWduwABcmY9jdOcnFo0MfaB5/xUgPYmKo8c1rETVBAWMXwTM/UseVeecH86RFfXDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f3b11f9b645317dccbcd37febfd45c65e7ff49dea3cf49968e643a45dcd2f6b2","last_reissued_at":"2026-05-18T00:38:18.699892Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:38:18.699892Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1606.05918","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":"2026-05-18T00:38:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L2HbAkq9w7I5oGK9ZbHaruNixHgLL9LethMtnosSfQYFXKPiJwFYIlJSVVW7XHxkIxZ7q4+d3MYSkdDE0avyAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T19:07:15.288376Z"},"content_sha256":"0c8af32efe1fea6f98746d04e80b5709776f888f0d9f1a379b16c703d8b1a520","schema_version":"1.0","event_id":"sha256:0c8af32efe1fea6f98746d04e80b5709776f888f0d9f1a379b16c703d8b1a520"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:6OYR7G3EKML5ZS6NG77L7VC4MX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Slack and Margin Rescaling as Convex Extensions of Supermodular Functions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM"],"primary_cat":"cs.LG","authors_text":"Matthew B. Blaschko","submitted_at":"2016-06-19T22:17:05Z","abstract_excerpt":"Slack and margin rescaling are variants of the structured output SVM, which is frequently applied to problems in computer vision such as image segmentation, object localization, and learning parts based object models. They define convex surrogates to task specific loss functions, which, when specialized to non-additive loss functions for multi-label problems, yield extensions to increasing set functions. We demonstrate in this paper that we may use these concepts to define polynomial time convex extensions of arbitrary supermodular functions, providing an analysis framework for the tightness o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.05918","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":""},"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":"2026-05-18T00:38:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+wOAjJ4GnqPYcTpJHK7OVung4Vx68GWLpiAQVPkX2+wtQcXaoOmQgeEENL5Qe+IWrBzOxttBYjrS+2YQc5lADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-07T19:07:15.289050Z"},"content_sha256":"6cda52b78e49d7162160e5474df46cb6d63e032b25d4fd3be1c8ffc49b3e134a","schema_version":"1.0","event_id":"sha256:6cda52b78e49d7162160e5474df46cb6d63e032b25d4fd3be1c8ffc49b3e134a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6OYR7G3EKML5ZS6NG77L7VC4MX/bundle.json","state_url":"https://pith.science/pith/6OYR7G3EKML5ZS6NG77L7VC4MX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6OYR7G3EKML5ZS6NG77L7VC4MX/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":"2026-06-07T19:07:15Z","links":{"resolver":"https://pith.science/pith/6OYR7G3EKML5ZS6NG77L7VC4MX","bundle":"https://pith.science/pith/6OYR7G3EKML5ZS6NG77L7VC4MX/bundle.json","state":"https://pith.science/pith/6OYR7G3EKML5ZS6NG77L7VC4MX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6OYR7G3EKML5ZS6NG77L7VC4MX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:6OYR7G3EKML5ZS6NG77L7VC4MX","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":"27758d43ded4eb7fc16849f4dbb37e7e45c95763e9fa5da68bca914fce381e0b","cross_cats_sorted":["cs.DM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-06-19T22:17:05Z","title_canon_sha256":"1b7ab948ab706f94e099c291cc06e7e0c5ce3272fa059f0b13975a0cecfb96a1"},"schema_version":"1.0","source":{"id":"1606.05918","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1606.05918","created_at":"2026-05-18T00:38:18Z"},{"alias_kind":"arxiv_version","alias_value":"1606.05918v2","created_at":"2026-05-18T00:38:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1606.05918","created_at":"2026-05-18T00:38:18Z"},{"alias_kind":"pith_short_12","alias_value":"6OYR7G3EKML5","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_16","alias_value":"6OYR7G3EKML5ZS6N","created_at":"2026-05-18T12:30:01Z"},{"alias_kind":"pith_short_8","alias_value":"6OYR7G3E","created_at":"2026-05-18T12:30:01Z"}],"graph_snapshots":[{"event_id":"sha256:6cda52b78e49d7162160e5474df46cb6d63e032b25d4fd3be1c8ffc49b3e134a","target":"graph","created_at":"2026-05-18T00:38:18Z","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":"Slack and margin rescaling are variants of the structured output SVM, which is frequently applied to problems in computer vision such as image segmentation, object localization, and learning parts based object models. They define convex surrogates to task specific loss functions, which, when specialized to non-additive loss functions for multi-label problems, yield extensions to increasing set functions. We demonstrate in this paper that we may use these concepts to define polynomial time convex extensions of arbitrary supermodular functions, providing an analysis framework for the tightness o","authors_text":"Matthew B. Blaschko","cross_cats":["cs.DM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-06-19T22:17:05Z","title":"Slack and Margin Rescaling as Convex Extensions of Supermodular Functions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1606.05918","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":"sha256:0c8af32efe1fea6f98746d04e80b5709776f888f0d9f1a379b16c703d8b1a520","target":"record","created_at":"2026-05-18T00:38:18Z","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":"27758d43ded4eb7fc16849f4dbb37e7e45c95763e9fa5da68bca914fce381e0b","cross_cats_sorted":["cs.DM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2016-06-19T22:17:05Z","title_canon_sha256":"1b7ab948ab706f94e099c291cc06e7e0c5ce3272fa059f0b13975a0cecfb96a1"},"schema_version":"1.0","source":{"id":"1606.05918","kind":"arxiv","version":2}},"canonical_sha256":"f3b11f9b645317dccbcd37febfd45c65e7ff49dea3cf49968e643a45dcd2f6b2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f3b11f9b645317dccbcd37febfd45c65e7ff49dea3cf49968e643a45dcd2f6b2","first_computed_at":"2026-05-18T00:38:18.699892Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:38:18.699892Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+cIZDHvvWenQAI16UQKntpWduwABcmY9jdOcnFo0MfaB5/xUgPYmKo8c1rETVBAWMXwTM/UseVeecH86RFfXDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:38:18.700624Z","signed_message":"canonical_sha256_bytes"},"source_id":"1606.05918","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0c8af32efe1fea6f98746d04e80b5709776f888f0d9f1a379b16c703d8b1a520","sha256:6cda52b78e49d7162160e5474df46cb6d63e032b25d4fd3be1c8ffc49b3e134a"],"state_sha256":"66e5d9d907812901d54b662c278f68228497cb4ee8d1599bceb2e70dfb88c957"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EZwdJ585EcA0QGGr05c09GE3Zq+AvQjtMkKM93ALmyOa2tUOXn4uMPs3RoWMqrONAyDnBajQ5LQtpGQSStaNAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-07T19:07:15.292999Z","bundle_sha256":"eb1a8f68b0a1a2dc32b6181b6dca239e5421d2b91bac6135572a3f03d8212959"}}