{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ERRJ7G6F6OIAKJVGGLYDK5R3AX","short_pith_number":"pith:ERRJ7G6F","canonical_record":{"source":{"id":"2010.10059","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T06:36:14Z","cross_cats_sorted":["cs.DM","stat.ML"],"title_canon_sha256":"5e37afc192fc6efe953f8a6d2ab9550cbec39e1d3806ae153c897f4ca8b398bc","abstract_canon_sha256":"88ea82ba58fdc541d02262607407323819fcf8d49d5ef9f0f311a194bd580c82"},"schema_version":"1.0"},"canonical_sha256":"24629f9bc5f3900526a632f035763b05ffa1155a7036db30eae95285b47bb4d4","source":{"kind":"arxiv","id":"2010.10059","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.10059","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.10059v5","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.10059","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"pith_short_12","alias_value":"ERRJ7G6F6OIA","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"pith_short_16","alias_value":"ERRJ7G6F6OIAKJVG","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"pith_short_8","alias_value":"ERRJ7G6F","created_at":"2026-07-05T02:38:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ERRJ7G6F6OIAKJVGGLYDK5R3AX","target":"record","payload":{"canonical_record":{"source":{"id":"2010.10059","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T06:36:14Z","cross_cats_sorted":["cs.DM","stat.ML"],"title_canon_sha256":"5e37afc192fc6efe953f8a6d2ab9550cbec39e1d3806ae153c897f4ca8b398bc","abstract_canon_sha256":"88ea82ba58fdc541d02262607407323819fcf8d49d5ef9f0f311a194bd580c82"},"schema_version":"1.0"},"canonical_sha256":"24629f9bc5f3900526a632f035763b05ffa1155a7036db30eae95285b47bb4d4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:38:30.880534Z","signature_b64":"8Ua6f8xzWW6xzibFiDgGMl9M8fO1YsPt8a9OBz0pamA+dOPPyCiqAoPyK+9ZvNJk80Kal5PkPtWBa4dwtMDwDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24629f9bc5f3900526a632f035763b05ffa1155a7036db30eae95285b47bb4d4","last_reissued_at":"2026-07-05T02:38:30.880065Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:38:30.880065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.10059","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:38:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iaJVuLcabzlumGVxkSoA4ZgxE/dMBdIMjhFvFO17IxgDEnBYsb5GPVAvTd7cdWz1Z31LFyX5/889TX058TIaDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:51:43.764491Z"},"content_sha256":"0115173118ddd3afed9ae6cff0908fa4e9316bfa3cee8e178aac585048bd9593","schema_version":"1.0","event_id":"sha256:0115173118ddd3afed9ae6cff0908fa4e9316bfa3cee8e178aac585048bd9593"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ERRJ7G6F6OIAKJVGGLYDK5R3AX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Very Fast Streaming Submodular Function Maximization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM","stat.ML"],"primary_cat":"cs.LG","authors_text":"Katharina Morik, Lukas Pfahler, Philipp-Jan Honysz, Sebastian Buschj\\\"ager","submitted_at":"2020-10-20T06:36:14Z","abstract_excerpt":"Data summarization has become a valuable tool in understanding even terabytes of data. Due to their compelling theoretical properties, submodular functions have been in the focus of summarization algorithms. These algorithms offer worst-case approximations guarantees to the expense of higher computation and memory requirements. However, many practical applications do not fall under this worst-case, but are usually much more well-behaved. In this paper, we propose a new submodular function maximization algorithm called ThreeSieves, which ignores the worst-case, but delivers a good solution in h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.10059","kind":"arxiv","version":5},"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/2010.10059/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":"2026-07-05T02:38:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+sGRRPUpDRh2rCcpTzStNIL1xsosoxa1xF5dzCXBqI2PXijp0ntNirsSejfJSCtX50BVVxFKZzi3FZmO0677Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:51:43.764996Z"},"content_sha256":"25599cdc5431993642b8d5a29d4a96dbaf283c5d3db28d372a20196431737700","schema_version":"1.0","event_id":"sha256:25599cdc5431993642b8d5a29d4a96dbaf283c5d3db28d372a20196431737700"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX/bundle.json","state_url":"https://pith.science/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX/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":"2026-08-20T21:51:43Z","links":{"resolver":"https://pith.science/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX","bundle":"https://pith.science/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX/bundle.json","state":"https://pith.science/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ERRJ7G6F6OIAKJVGGLYDK5R3AX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ERRJ7G6F6OIAKJVGGLYDK5R3AX","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":"88ea82ba58fdc541d02262607407323819fcf8d49d5ef9f0f311a194bd580c82","cross_cats_sorted":["cs.DM","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T06:36:14Z","title_canon_sha256":"5e37afc192fc6efe953f8a6d2ab9550cbec39e1d3806ae153c897f4ca8b398bc"},"schema_version":"1.0","source":{"id":"2010.10059","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.10059","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.10059v5","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.10059","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"pith_short_12","alias_value":"ERRJ7G6F6OIA","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"pith_short_16","alias_value":"ERRJ7G6F6OIAKJVG","created_at":"2026-07-05T02:38:30Z"},{"alias_kind":"pith_short_8","alias_value":"ERRJ7G6F","created_at":"2026-07-05T02:38:30Z"}],"graph_snapshots":[{"event_id":"sha256:25599cdc5431993642b8d5a29d4a96dbaf283c5d3db28d372a20196431737700","target":"graph","created_at":"2026-07-05T02:38:30Z","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/2010.10059/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data summarization has become a valuable tool in understanding even terabytes of data. Due to their compelling theoretical properties, submodular functions have been in the focus of summarization algorithms. These algorithms offer worst-case approximations guarantees to the expense of higher computation and memory requirements. However, many practical applications do not fall under this worst-case, but are usually much more well-behaved. In this paper, we propose a new submodular function maximization algorithm called ThreeSieves, which ignores the worst-case, but delivers a good solution in h","authors_text":"Katharina Morik, Lukas Pfahler, Philipp-Jan Honysz, Sebastian Buschj\\\"ager","cross_cats":["cs.DM","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T06:36:14Z","title":"Very Fast Streaming Submodular Function Maximization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.10059","kind":"arxiv","version":5},"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":"sha256:0115173118ddd3afed9ae6cff0908fa4e9316bfa3cee8e178aac585048bd9593","target":"record","created_at":"2026-07-05T02:38:30Z","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":"88ea82ba58fdc541d02262607407323819fcf8d49d5ef9f0f311a194bd580c82","cross_cats_sorted":["cs.DM","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-20T06:36:14Z","title_canon_sha256":"5e37afc192fc6efe953f8a6d2ab9550cbec39e1d3806ae153c897f4ca8b398bc"},"schema_version":"1.0","source":{"id":"2010.10059","kind":"arxiv","version":5}},"canonical_sha256":"24629f9bc5f3900526a632f035763b05ffa1155a7036db30eae95285b47bb4d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"24629f9bc5f3900526a632f035763b05ffa1155a7036db30eae95285b47bb4d4","first_computed_at":"2026-07-05T02:38:30.880065Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:38:30.880065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8Ua6f8xzWW6xzibFiDgGMl9M8fO1YsPt8a9OBz0pamA+dOPPyCiqAoPyK+9ZvNJk80Kal5PkPtWBa4dwtMDwDg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:38:30.880534Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.10059","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0115173118ddd3afed9ae6cff0908fa4e9316bfa3cee8e178aac585048bd9593","sha256:25599cdc5431993642b8d5a29d4a96dbaf283c5d3db28d372a20196431737700"],"state_sha256":"a0be6cfa22c09bd6ff9ddf5c9e3cbf886edec20c05f586f3f51fed6bde70b862"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2PztyoDWhqynH91VRXdyC1xggxJAnW8pNfw1GIU2PeucNeyrGKHHQ3kWSPm3XcYgp545IN+gOdAsyEv0H56zBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T21:51:43.768756Z","bundle_sha256":"e7d03e8641ba4c1cda1f2f734e0defa35eea5a92b16d1674dbde5017d3d971e6"}}